Phoster

Research and Development

Neurosymbolic Mental Simulation and Imagination

Introduction

A Neural-symbolic Framework for Mental Simulation by Michael Kissner, Simulation as an Engine of Physical Scene Understanding by Peter W. Battaglia, Jessica B. Hamrick and Joshua B. Tenenbaum, Analogues of Mental Simulation and Imagination in Deep Learning by Jessica B. Hamrick and Imagination Machines: A New Challenge for Artificial Intelligence by Sridhar Mahadevan.

Model Learning

Interaction Networks for Learning about Objects, Relations and Physics by Peter Battaglia, Razvan Pascanu, Matthew Lai and Danilo J. Rezende, Visual Interaction Networks: Learning a Physics Simulator from Video by Nicholas Watters, Daniel Zoran, Theophane Weber, Peter Battaglia, Razvan Pascanu and Andrea Tacchetti, Unsupervised Intuitive Physics from Visual Observations by Sebastien Ehrhardt, Aron Monszpart, Niloy Mitra and Andrea Vedaldi, End-to-end Differentiable Physics for Learning and Control by Filipe de Avila Belbute-Peres, Kevin Smith, Kelsey Allen, Josh Tenenbaum and J. Zico Kolter, Neural Relational Inference for Interacting Systems by Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling and Richard Zemel, Physics-as-inverse-graphics: Joint Unsupervised Learning of Objects and Physics from Video by Miguel Jaques, Michael Burke and Timothy Hospedales, Physics-as-inverse-graphics: Unsupervised Physical Parameter Estimation from Video by Miguel Jaques, Michael Burke and Timothy Hospedales, Flexible Neural Representation for Physics Prediction by Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li F. Fei-Fei, Josh Tenenbaum and Daniel L. Yamins, Learning Predictive Models from Observation and Interaction by Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine and Chelsea Finn and Causal Discovery in Physical Systems from Videos by Yunzhu Li, Antonio Torralba, Animashree Anandkumar, Dieter Fox and Animesh Garg.

Symbolic Regression

Deep Symbolic Regression: Recovering Mathematical Expressions from Data via Policy Gradients by Brenden K. Petersen, Learning Symbolic Physics with Graph Networks by Miles D. Cranmer, Rui Xu, Peter Battaglia and Shirley Ho, Discovering Symbolic Models from Deep Learning with Inductive Biases by Miles D. Cranmer, Alvaro Sanchez-Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer, David Spergel and Shirley Ho and AI Feynman: A Physics-inspired Method for Symbolic Regression by Silviu-Marian Udrescu and Max Tegmark.

Episodic Working Memory

From Deep Learning to Episodic Memories: Creating Categories of Visual Experiences by Jigar Doshi, Zsolt Kira and Alan Wagner, Neural Episodic Control by Alexander Pritzel, Benigno Uria, Sriram Srinivasan, Adria Puigdomènech, Oriol Vinyals, Demis Hassabis, Daan Wierstra and Charles Blundell, Generalization of Reinforcement Learners with Working and Episodic Memory by Meire Fortunato, Melissa Tan, Ryan Faulkner, Steven Hansen, Adrià P. Badia, Gavin Buttimore, Charles Deck, Joel Z. Leibo and Charles Blundell and MEMO: A Deep Network for Flexible Combination of Episodic Memories by Andrea Banino, Adrià P. Badia, Raphael Köster, Martin J. Chadwick, Vinicius Zambaldi, Demis Hassabis, Caswell Barry, Matthew Botvinick, Dharshan Kumaran and Charles Blundell.

Semantic Working Memory

Semantic Memory Modeling and Memory Interaction in Learning Agents by Wenwen Wang, Ah-Hwee Tan and Loo-Nin Teow.

Visuospatial Working Memory

Neural Scene Representation and Rendering by S. M. Ali Eslami, Danilo J. Rezende, Frederic Besse, Fabio Viola, Ari S. Morcos, Marta Garnelo, Avraham Ruderman, Andrei A. Rusu, Ivo Danihelka, Karol Gregor, David P. Reichert, Lars Buesing, Theophane Weber, Oriol Vinyals, Dan Rosenbaum, Neil Rabinowitz, Helen King, Chloe Hillier, Matt Botvinick, Daan Wierstra, Koray Kavukcuoglu and Demis Hassabis.

Reinforcement Learning

Metacontrol for Adaptive Imagination-based Optimization by Jessica B. Hamrick, Andrew J. Ballard, Razvan Pascanu, Oriol Vinyals, Nicolas Heess and Peter W. Battaglia, Imagination-augmented Agents for Deep Reinforcement Learning by Théophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Rezende, Adria P. Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter Battaglia, Demis Hassabis, David Silver and Daan Wierstra, Recurrent Environment Simulators by Silvia Chiappa, Sébastien Racaniere, Daan Wierstra and Shakir Mohamed and Recurrent World Models Facilitate Policy Evolution by David Ha and Jürgen Schmidhuber.

Simulation

Computational Mechanics Enhanced by Deep Learning by Atsuya Oishi and Genki Yagawa, Physics-informed Neural Networks: A Deep Learning Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential Equations by Maziar Raissi, Paris Perdikaris and George E. Karniadakis, Towards Finite Element Simulation Using Deep Learning by Francois Roewer-Despres, Najeeb Khan and Ian Stavness and Finite Element Network Analysis: A Machine Learning Based Computational Framework for the Simulation of Physical Systems by Mehdi Jokar and Fabio Semperlotti.

Verification and Validation

Verification and Validation of Simulation Models by Robert G. Sargent.

Design and Engineering

3D Design Using Generative Adversarial Networks and Physics-based Validation by Dule Shu, James Cunningham, Gary Stump, Simon W. Miller, Michael A. Yukish, Timothy W. Simpson and Conrad S. Tucker, A Physics-based Virtual Environment for Enhancing the Quality of Deep Generative Designs by Matthew Dering, James Cunningham, Raj Desai, Michael A. Yukish, Timothy W. Simpson and Conrad S. Tucker, Generative Design by Reinforcement Learning: Maximizing Diversity of Topology Optimized Designs by Seowoo Jang and Namwoo Kang, Synthesizing Designs with Interpart Dependencies Using Hierarchical Generative Adversarial Networks by Wei Chen and Mark Fuge, Design Space Exploration Using Constraint Satisfaction by Noel Titus and Karthik Ramani, Using Constraint Satisfaction for Designing Mechanical Systems by Pierre-Alain Yvars, Model Agnostic Solution of CSPs via Deep Learning: A Preliminary Study by Andrea Galassi, Michele Lombardi, Paola Mello and Michela Milano and Towards Effective Deep Learning for Constraint Satisfaction Problems by Hong Xu, Sven Koenig and T. K. Satish Kumar.

Art

Rating Image Aesthetics Using Deep Learning by Xin Lu, Zhe Lin, Hailin Jin, Jianchao Yang and James Z. Wang, Reinforcement Learning for Generative Art by Jieliang Luo, Multi-criteria Reinforcement Learning by Zoltán Gábor, Zsolt Kalmár and Csaba Szepesvári, Evolving Art Using Multiple Aesthetic Measures by Eelco den Heijer and A. E. Eiben and Learning Aesthetic Judgements in Evolutionary Art Systems by Yang Li, Changjun Hu, Leandro L. Minku and Haolei Zuo.

Neurosymbolic Narrative Intelligence

Introduction

Narrative Intelligence edited by Michael Mateas and Phoebe Sengers and Computational Narrative Intelligence: A Human-centered Goal for Artificial Intelligence by Mark O. Riedl.

Narrative Question Answering

The NarrativeQA Reading Comprehension Challenge by Tomáš Kočiský, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis and Edward Grefenstette, A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories by Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli and James F. Allen, MovieQA: Understanding Stories in Movies through Question-answering by Makarand Tapaswi, Yukun Zhu, Rainer Stiefelhagen, Antonio Torralba, Raquel Urtasun and Sanja Fidler, MarioQA: Answering Questions by Watching Gameplay Videos by Jonghwan Mun, Paul Hongsuck Seo, Ilchae Jung and Bohyung Han, DramaQA: Character-centered Video Story Understanding with Hierarchical QA by Seongho Choi, Kyoung-Woon On, Yu-Jung Heo, Ahjeong Seo, Youwon Jang, Seungchan Lee, Minsu Lee and Byoung-Tak Zhang, Social-IQ: A Question Answering Benchmark for Artificial Social Intelligence by Amir Zadeh, Michael Chan, Paul Pu Liang, Edmund Tong and Louis-Philippe Morency, Evaluating Theory of Mind in Question Answering by Aida Nematzadeh, Kaylee Burns, Erin Grant, Alison Gopnik and Thomas L. Griffiths, Revisiting the Evaluation of Theory of Mind through Question Answering by Matthew Le, Y-Lan Boureau and Maximilian Nickel, A Read-write Memory Network for Movie Story Understanding by Seil Na, Sangho Lee, Jisung Kim and Gunhee Kim, Multimodal Dual Attention Memory for Video Story Question Answering by Kyung-Min Kim, Seong-Ho Choi, Jin-Hwa Kim and Byoung-Tak Zhang, Movie Question Answering: Remembering the Textual Cues for Layered Visual Contents by Bo Wang, Youjiang Xu, Yahong Han and Richang Hong, Progressive Attention Memory Network for Movie Story Question Answering by Junyeong Kim, Minuk Ma, Kyungsu Kim, Sungjin Kim and Chang D. Yoo and DeepStory: Video Story QA by Deep Embedded Memory Networks by Kyung-Min Kim, Min-Oh Heo, Seong-Ho Choi and Byoung-Tak Zhang.

Narrative Prediction

Neural Networks for Narrative Continuation by Melissa Roemmele, An Encoder-decoder Approach to Predicting Causal Relations in Stories by Melissa Roemmele and Andrew Gordon and Learning to Predict Explainable Plots for Neural Story Generation by Gang Chen, Yang Liu, Huanbo Luan, Meng Zhang, Qun Liu and Maosong Sun.

Narrative Generation

Hierarchical Neural Story Generation by Angela Fan, Mike Lewis and Yann Dauphin, Controllable Neural Story Plot Generation via Reinforcement Learning by Pradyumna Tambwekar, Murtaza Dhuliawala, Lara J. Martin, Animesh Mehta, Brent Harrison and Mark O. Riedl, A Character-centric Neural Model for Automated Story Generation by Danyang Liu, Juntao Li, Meng-Hsuan Yu, Ziming Huang, Gongshen Liu, Dongyan Zhao and Rui Yan, Event Representations for Automated Story Generation with Deep Neural Nets by Lara J. Martin, Prithviraj Ammanabrolu, Xinyu Wang, William Hancock, Shruti Singh, Brent Harrison and Mark O. Riedl, Story Realization: Expanding Plot Events into Sentences by Prithviraj Ammanabrolu, Ethan Tien, Wesley Cheung, Zhaochen Luo, William Ma, Lara J. Martin and Mark O. Riedl and Guided Neural Language Generation for Automated Storytelling by Prithviraj Ammanabrolu, Ethan Tien, Wesley Cheung, Zhaochen Luo, William Ma, Lara J. Martin and Mark O. Riedl.

Interactive Narrative Generation

Toward Automated Quest Generation in Text-adventure Games by Prithviraj Ammanabrolu, William Broniec, Alex Mueller, Jeremy Paul and Mark O. Riedl, Bringing Stories Alive: Generating Interactive Fiction Worlds by Prithviraj Ammanabrolu, Wesley Cheung, Dan Tu, William Broniec and Mark O. Riedl, Generating Interactive Worlds with Text by Angela Fan, Jack Urbanek, Pratik Ringshia, Emily Dinan, Emma Qian, Siddharth Karamcheti, Shrimai Prabhumoye, Douwe Kiela, Tim Rocktäschel, Arthur Szlam and Jason Weston, Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation by Niels Justesen, Ruben Rodriguez Torrado, Philip Bontrager, Ahmed Khalifa, Julian Togelius and Sebastian Risi, Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning by Arthur Juliani, Ahmed Khalifa, Vincent-Pierre Berges, Jonathan Harper, Ervin Teng, Hunter Henry, Adam Crespi, Julian Togelius and Danny Lange, The Animal-AI Environment: Training and Testing Animal-like Artificial Cognition by Benjamin Beyret, José Hernández-Orallo, Lucy Cheke, Marta Halina, Murray Shanahan and Matthew Crosby, Procedural Content Generation: From Automatically Generating Game Levels to Increasing Generality in Machine Learning by Sebastian Risi and Julian Togelius, Strategically Training and Evaluating Agents in Procedurally Generated Environments by Richard Everett and Optimising Worlds to Evaluate and Influence Reinforcement Learning Agents by Richard Everett, Adam Cobb, Andrew Markham and Stephen Roberts.

Interactive Narrative Playing

Playing Text-adventure Games with Graph-based Deep Reinforcement Learning by Prithviraj Ammanabrolu and Mark O. Riedl, Comprehensible Context-driven Text Game Playing by Xusen Yin and Jonathan May, NAIL: A General Interactive Fiction Agent by Matthew Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan and Jason D. Williams, Playing Atari with Deep Reinforcement Learning by Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra and Martin Riedmiller, Human-level Control through Deep Reinforcement Learning by Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg and Demis Hassabis, Deep Learning for Video Game Playing by Niels Justesen, Philip Bontrager, Julian Togelius and Sebastian Risi and A Survey of Deep Reinforcement Learning in Video Games by Kun Shao, Zhentao Tang, Yuanheng Zhu, Nannan Li and Dongbin Zhao.

Narrative Visualization

Contextualize, Show and Tell: A Neural Visual Storyteller by Diana Gonzalez-Rico and Gibran Fuentes-Pineda, Show Me a Story: Towards Coherent Neural Story Illustration by Hareesh Ravi, Lezi Wang, Carlos Muniz, Leonid Sigal, Dimitris Metaxas and Mubbasir Kapadia, Neural Storyboard Artist: Visualizing Stories with Coherent Image Sequences by Shizhe Chen, Bei Liu, Jianlong Fu, Ruihua Song, Qin Jin, Pingping Lin, Xiaoyu Qi, Chunting Wang and Jin Zhou and StoryGAN: A Sequential Conditional GAN for Story Visualization by Yitong Li, Zhe Gan, Yelong Shen, Jingjing Liu, Yu Cheng, Yuexin Wu, Lawrence Carin, David Carlson and Jianfeng Gao.

Narrative Transcription

Video Description: A Survey of Methods, Datasets, and Evaluation Metrics by Nayyer Aafaq, Ajmal Mian, Wei Liu, Syed Z. Gilani and Mubarak Shah, Grounded Video Description by Luowei Zhou, Yannis Kalantidis, Xinlei Chen, Jason J. Corso and Marcus Rohrbach, Translating Video Content to Natural Language Descriptions by Marcus Rohrbach, Wei Qiu, Ivan Titov, Stefan Thater, Manfred Pinkal and Bernt Schiele, Translating Videos to Natural Language using Deep Recurrent Neural Networks by Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond Mooney and Kate Saenko, Towards Coherent Natural Language Description of Video Streams by Muhammad U. G. Khan, Lei Zhang and Yoshihiko Gotoh, Coherent Multi-sentence Video Description with Variable Level of Detail by Anna Rohrbach, Marcus Rohrbach, Wei Qiu, Annemarie Friedrich, Manfred Pinkal and Bernt Schiele, Verbalization of 3D Scenes Based on Natural Language Generation Techniques by Vassilios Golfinopoulos, Dimitrios Makris, Georgios Bardis, Georgios Miaoulis and Dimitri Plemenos, From the Event Log of a Social Simulation to Narrative Discourse: Content Planning in Story Generation by Carlos León, Samer Hassan and Pablo Gervás, The "Inverse Hollywood Problem": From Video to Scripts and Storyboards via Causal Analysis by Matthew Brand, The Visuospatial Dimension of Writing by Thierry Olive and Jean-Michel Passerault, Verbal, Visual, and Spatial Working Memory in Written Language Production by Ronald T. Kellogg, Thierry Olive and Annie Piolat, Verbal, Visual, and Spatial Working Memory Demands During Text Composition by Thierry Olive, Ronald T. Kellogg and Annie Piolat and The Contribution of Different Components of Working Memory to Knowledge Transformation During Writing by David Galbraith, Sheila Ford, Gillian Walker and Jessica Ford.

Narrative Summarization

Summarizing Narratives by Wendy G. Lohnert, John B. Black and Brian J. Reiser, Narrative Summarization by Inderjeet Mani, A Framework for Summarizing Game Experiences as Narratives by Yun-Gyung Cheong and R. Michael Young, Automatized Summarization of Multiplayer Games by Peter Mindek, Ivan Viola, Eduard Gröller and Stefan Bruckner, Action Summary for Computer Games: Extracting Action for Spectator Modes and Summaries by Nick Halper and Maic Masuch, Automated Creation of Movie Summaries in Interactive Virtual Environments by Doron Friedman, Ariel Shamir, Yishai Feldman and Tsvi Dagan and Coherent Narrative Summarization with a Cognitive Model by Renxian Zhang, Wenjie Li, Naishi Liu and Dehong Gao.

Neurosymbolic Learning and Reasoning

Introduction

Neural-symbolic Learning and Reasoning: A Survey and Interpretation by Tarek R. Besold, Artur S. d'Avila Garcez, Sebastian Bader, Howard Bowman, Pedro Domingos, Pascal Hitzler, Kai-Uwe Kühnberger, Luis C. Lamb, Daniel Lowd, Priscila M. V. Lima, Leo de Penning, Gadi Pinkas, Hoifung Poon and Gerson Zaverucha, Dimensions of Neural-symbolic Integration - A Structured Survey by Sebastian Bader and Pascal Hitzler, Computational Architectures Integrating Neural and Symbolic Processes: A Perspective on the State of the Art edited by Ron Sun and Lawrence A. Bookman, Connectionist-symbolic Integration: From Unified to Hybrid Approaches by Ron Sun and Frederic Alexandre, Hybrid Neural Systems edited by Ron Sun and Stefan Wermter, Neural-symbolic Cognitive Reasoning by Artur S. d'Avila Garcez, Luis C. Lamb and Dov M. Gabbay, Perspectives of Neural-symbolic Integration edited by Barbara Hammer and Pascal Hitzler, Neural-symbolic Learning Systems: Foundations and Applications by Artur S. d'Avila Garcez, Krysia B. Broda and Dov M. Gabbay and What Can Neural Networks Reason About? by Keyulu Xu, Jingling Li, Mozhi Zhang, Simon S. Du, Ken-ichi Kawarabayashi and Stefanie Jegelka.

Knowledge Representation

Cognitive Algorithms and Systems: Reasoning and Knowledge Representation by Artur S. d'Avila Garcez and Luis C. Lamb, Reconciling Deep Learning with Symbolic Artificial Intelligence: Representing Objects and Relations by Marta Garnelo and Murray Shanahan, A Model for Structured Information Representation in Neural Networks by Michael G. Müller, Christos H. Papadimitriou, Wolfgang Maass and Robert Legenstein, Learning Task-general Representations with Generative Neuro-symbolic Modeling by Reuben Feinman and Brenden M. Lake and Generating New Concepts with Hybrid Neuro-symbolic Models by Reuben Feinman and Brenden M. Lake.

Logic

Logic Programs and Connectionist Networks by Pascal Hitzler, Steffen Hölldobler and Anthony K. Seda, Approximating the Semantics of Logic Programs by Recurrent Neural Networks by Steffen Hölldobler, Yvonne Kalinke and Hans-Peter Störr, The Connectionist Inductive Learning and Logic Programming System by Artur S. d'Avila Garcez and Gerson Zaverucha, A Connectionist Model of Unification by Andreas Stolcke, Unification as Constraint Satisfaction in Structured Connectionist Networks by Andreas Stolcke, Unification in Prolog by Connectionist Models by Volker Weber, A Structured Connectionist Unification Algorithm by Steffen Hölldobler, Connectionist Variable Binding by Antony Browne and Ron Sun, DeepLogic: Towards End-to-end Differentiable Logical Reasoning by Nuri Cingillioglu and Alessandra Russo, DeepProbLog: Neural Probabilistic Logic Programming by Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester and Luc de Raedt, Logic Programs with Uncertainty: Neural Computations and Automated Reasoning by Ekaterina Komendantskaya and Anthony K. Seda, Neural-symbolic Intuitionistic Reasoning by Artur S. d'Avila Garcez, Luis C. Lamb and Dov M. Gabbay, Connectionist Modal Logic: Representing Modalities in Neural Networks by Artur S. d'Avila Garcez, Luis C. Lamb and Dov M. Gabbay, Advances in Neural-symbolic Learning Systems: Modal and Temporal Reasoning by Artur S. d'Avila Garcez, Connectionist Inference Models by Antony Browne and Ron Sun, Connectionist Representation of Multi-valued Logic Programs by Ekaterina Komendantskaya, Máire Lane and Anthony K. Seda, Connectionist Model Generation: A First-order Approach by Sebastian Bader, Pascal Hitzler and Steffen Hölldobler, Neural Logic Machines by Honghua Dong, Jiayuan Mao, Tian Lin, Chong Wang, Lihong Li and Denny Zhou, Integrating Learning and Reasoning with Deep Logic Models by Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti and Marco Gori, Extracting Reduced Logic Programs from Artificial Neural Networks by Jens Lehmann, Sebastian Bader and Pascal Hitzler, A Neural Network Model of Causality by Ron Sun, Abductive Reasoning in Neural-symbolic Systems by Artur S. d'Avila Garcez, Dov M. Gabbay, Oliver Ray and John Woods and A Neural Network Approach for First-order Abductive Inference by Oliver Ray and Bruno Golénia.

Mathematics

Analysing Mathematical Reasoning Abilities of Neural Models by David Saxton, Edward Grefenstette, Felix Hill and Pushmeet Kohli, End-to-end Differentiable Proving by Tim Rocktäschel and Sebastian Riedel and Deep Learning for Symbolic Mathematics by Guillaume Lample and François Charton.

Argumentation

Argumentation Neural Networks by Artur S. d'Avila Garcez, Dov M. Gabbay and Luís C. Lamb, Argumentation Frameworks as Neural Networks by Artur S. d'Avila Garcez, Luís C. Lamb and Dov M. Gabbay and Fibring Argumentation Frames by Dov M. Gabbay.

Constraint Satisfaction

Model Agnostic Solution of CSPs via Deep Learning: A Preliminary Study by Andrea Galassi, Michele Lombardi, Paola Mello and Michela Milano, Towards Effective Deep Learning for Constraint Satisfaction Problems by Hong Xu, Sven Koenig and T. K. Satish Kumar and PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers by Saeed Amizadeh, Sergiy Matusevych and Markus Weimer.

Program Synthesis

Neural Programmer-interpreters by Scott Reed and Nando de Freitas, Neuro-symbolic Program Synthesis by Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, Lihong Li, Dengyong Zhou and Pushmeet Kohli, DeepCoder: Learning to Write Programs by Matej Balog, Alexander L. Gaunt, Marc Brockschmidt, Sebastian Nowozin and Daniel Tarlow, Neural Program Search: Solving Programming Tasks from Description and Examples by Illia Polosukhin and Alexander Skidanov and Program Synthesis from Natural Language Using Recurrent Neural Networks by Xi V. Lin, Chenglong Wang, Deric Pang, Kevin Vu and Michael D. Ernst.

Fibring

Fibring Neural Networks by Artur S. d'Avila Garcez and Dov M. Gabbay, Computing First-order Logic Programs by Fibring Artificial Neural Networks by Sebastian Bader, Artur S. d'Avila Garcez and Pascal Hitzler and Computation of Normal Logic Programs by Fibring Neural Networks by Vladimir Komendantsky and Anthony K. Seda.

Modularity

Modular Neural Networks: A Survey by Gasser Auda and Mohamed Kamel, Design and Evolution of Modular Neural Network Architectures by Bart L. M. Happel and Jacob M. J. Murre, Biologically Inspired Modular Neural Networks by Farooq Azam and A Review of Modularization Techniques in Artificial Neural Networks by Mohammed Amer and Tomás Maul.

Neurosymbolic Multimodal Intelligence

Introduction

Multimodal Intelligence: Representation Learning, Information Fusion, and Applications by Chao Zhang, Zichao Yang, Xiaodong He and Li Deng, Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods by Aditya Mogadala, Marimuthu Kalimuthu and Dietrich Klakow, Multimodal Machine Learning: A Survey and Taxonomy by Tadas Baltrušaitis, Chaitanya Ahuja and Louis-Philippe Morency and Deep Audio-visual Learning: A Survey by Hao Zhu, Mandi Luo, Rui Wang, Aihua Zheng and Ran He.

Image Description

A Survey on Automatic Image Caption Generation by Shuang Bai and Shan An, A Comprehensive Survey of Deep Learning for Image Captioning by M. D. Zakir Hossain, Ferdous Sohel, Mohd F. Shiratuddin and Hamid Laga, Show and Tell: A Neural Image Caption Generator by Oriol Vinyals, Alexander Toshev, Samy Bengio and Dumitru Erhan, Show, Attend and Tell: Neural Image Caption Generation with Visual Attention by Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel and Yoshua Bengio, Unifying Visual-semantic Embeddings with Multimodal Neural Language Models by Ryan Kiros, Ruslan Salakhutdinov and Richard S. Zemel and Deep Visual-semantic Alignments for Generating Image Descriptions by Andrej Karpathy and Li Fei-Fei.

Visual Question Answering

VQA: Visual Question Answering by Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C. Lawrence Zitnick and Devi Parikh.

Reasoning

Neural Module Networks by Jacob Andreas, Marcus Rohrbach, Trevor Darrell and Dan Klein, A Simple Neural Network Module for Relational Reasoning by Adam Santoro, David Raposo, David G. Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia and Timothy Lillicrap, Inferring and Executing Programs for Visual Reasoning by Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Judy Hoffman, Li Fei-Fei, C. Lawrence Zitnick and Ross Girshick, Neural-symbolic VQA: Disentangling Reasoning from Vision and Language Understanding by Kexin Yi, Jiajun Wu, Chuang Gan, Antonio Torralba, Pushmeet Kohli and Joshua B. Tenenbaum, FiLM: Visual Reasoning with a General Conditioning Layer by Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin and Aaron Courville, Compositional Attention Networks for Machine Reasoning by Drew A. Hudson and Christopher D. Manning, Explainable Neural Computation via Stack Neural Module Networks by Ronghang Hu, Jacob Andreas, Trevor Darrell and Kate Saenko, Transparency by Design: Closing the Gap between Performance and Interpretability in Visual Reasoning by David Mascharka, Philip Tran, Ryan Soklaski and Arjun Majumdar and The Neuro-symbolic Concept Learner: Interpreting Scenes, Words, and Sentences from Natural Supervision by Jiayuan Mao, Chuang Gan, Pushmeet Kohli, Joshua B. Tenenbaum and Jiajun Wu.

Knowledge

Improving Question Answering with External Knowledge by Xiaoman Pan, Kai Sun, Dian Yu, Jianshu Chen, Heng Ji, Claire Cardie and Dong Yu, KVQA: Knowledge-aware Visual Question Answering by Sanket Shah, Anand Mishra, Naganand Yadati and Partha P. Talukdar, OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge by Kenneth Marino, Mohammad Rastegari, Ali Farhadi and Roozbeh Mottaghi and Natural Language QA Approaches Using Reasoning with External Knowledge by Chitta Baral, Pratyay Banerjee, Kuntal Kumar Pal and Arindam Mitra.

Scene Graph Generation

Explainable and Explicit Visual Reasoning over Scene Graphs by Jiaxin Shi, Hanwang Zhang and Juanzi Li, An Empirical Study on Leveraging Scene Graphs for Visual Question Answering by Cheng Zhang, Wei-Lun Chao and Dong Xuan, Neural Motifs: Scene Graph Parsing with Global Context by Rowan Zellers, Mark Yatskar, Sam Thomson and Yejin Choi, Scene Graph Generation with External Knowledge and Image Reconstruction by Jiuxiang Gu, Handong Zhao, Zhe Lin, Sheng Li, Jianfei Cai and Mingyang Ling, Differentiable Scene Graphs by Moshiko Raboh, Roei Herzig, Jonathan Berant, Gal Chechik and Amir Globerson and Attentive Relational Networks for Mapping Images to Scene Graphs by Mengshi Qi, Weijian Li, Zhengyuan Yang, Yunhong Wang and Jiebo Luo.

Image Transformation

Image Super-resolution by Neural Texture Transfer by Zhifei Zhang, Zhaowen Wang, Zhe Lin and Hairong Qi, Image Style Transfer Using Convolutional Neural Networks by Leon A. Gatys, Alexander S. Ecker and Matthias Bethge and High-resolution Image Synthesis and Semantic Manipulation with Conditional GANs by Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Andrew Tao, Jan Kautz and Bryan Catanzaro.

Image Generation

Visualizing Natural Language Descriptions: A Survey by Kaveh Hassani and Won-Sook Lee, Generating Images from Captions with Attention by Elman Mansimov, Emilio Parisotto, Jimmy Lei Ba and Ruslan Salakhutdinov, Generative Adversarial Text to Image Synthesis by Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele and Honglak Lee, StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks by Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang and Dimitris N. Metaxas, Parallel Multiscale Autoregressive Density Estimation by Scott Reed, Aäron van den Oord, Nal Kalchbrenner, Sergio G. Colmenarejo, Ziyu Wang, Yutian Chen, Dan Belov and Nando de Freitas, Scene Graph Generation with External Knowledge and Image Reconstruction by Jiuxiang Gu, Handong Zhao, Zhe Lin, Sheng Li, Jianfei Cai and Mingyang Ling and Image Generation from Scene Graphs by Justin Johnson, Agrim Gupta and Li Fei-Fei.

Video Description

Video Description: A Survey of Methods, Datasets, and Evaluation Metrics by Nayyer Aafaq, Ajmal Mian, Wei Liu, Syed Z. Gilani and Mubarak Shah, Grounded Video Description by Luowei Zhou, Yannis Kalantidis, Xinlei Chen, Jason J. Corso and Marcus Rohrbach, Translating Video Content to Natural Language Descriptions by Marcus Rohrbach, Wei Qiu, Ivan Titov, Stefan Thater, Manfred Pinkal and Bernt Schiele and Translating Videos to Natural Language using Deep Recurrent Neural Networks by Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond Mooney and Kate Saenko.

Video Question Answering

TGIF-QA: Toward Spatio-temporal Reasoning in Visual Question Answering by Yunseok Jang, Yale Song, Youngjae Yu, Youngjin Kim and Gunhee Kim, MarioQA: Answering Questions by Watching Gameplay Videos by Jonghwan Mun, Paul Hongsuck Seo, Ilchae Jung and Bohyung Han, TVQA: Localized, Compositional Video Question Answering by Jie Lei, Licheng Yu, Mohit Bansal and Tamara L. Berg, Explore Multi-step Reasoning in Video Question Answering by Xiaomeng Song, Yucheng Shi, Xin Chen and Yahong Han, Video Question Answering via Hierarchical Spatio-temporal Attention Networks by Zhou Zhao, Qifan Yang, Deng Cai, Xiaofei He and Yueting Zhuang, Uncovering the Temporal Context for Video Question Answering by Linchao Zhu, Zhongwen Xu, Yi Yang and Alexander G. Hauptmann and Multi-turn Video Question Answering via Multi-stream Hierarchical Attention Context Network by Zhou Zhao, Xinghua Jiang, Deng Cai, Jun Xiao, Xiaofei He and Shiliang Pu.

Video Transformation

Video Super Resolution Based on Deep Learning: A Comprehensive Survey by Hongying Liu, Zhubo Ruan, Peng Zhao, Fanhua Shang, Linlin Yang and Yuanyuan Liu, Learning Temporal Coherence via Self-supervision for GAN-based Video Generation by Mengyu Chu, You Xie, Jonas Mayer, Laura Leal-Taixé and Nils Thuerey, Artistic Style Transfer for Videos by Manuel Ruder, Alexey Dosovitskiy and Thomas Brox, Real-time Neural Style Transfer for Videos by Haozhi Huang, Hao Wang, Wenhan Luo, Lin Ma, Wenhao Jiang, Xiaolong Zhu, Zhifeng Li and Wei Liu, Video-to-video Synthesis by Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Guilin Liu, Andrew Tao, Jan Kautz and Bryan Catanzaro and World-consistent Video-to-video Synthesis by Arun Mallya, Ting-Chun Wang, Karan Sapra and Ming-Yu Liu.

Video Generation

Conditional GAN with Discriminative Filter Generation for Text-to-video Synthesis by Yogesh Balaji, Martin Renqiang Min, Bing Bai, Rama Chellappa and Hans P. Graf, TFGAN: Improving Conditioning for Text-to-video Synthesis by Yogesh Balaji, Martin Renqiang Min, Bing Bai, Rama Chellappa and Hans P. Graf and Cross-modal Dual Learning for Sentence-to-video Generation by Yue Liu, Xin Wang, Yitian Yuan and Wenwu Zhu.

Audio Description

Automated Audio Captioning with Recurrent Neural Networks by Konstantinos Drossos, Sharath Adavanne and Tuomas Virtanen, Neural Audio Captioning Based on Conditional Sequence-to-sequence Model by Shota Ikawa and Kunio Kashino and Audio Caption: Listen and Tell by Mengyue Wu, Heinrich Dinkel and Kai Yu.

Audio Generation

WaveNet: A Generative Model for Raw Audio by Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior and Koray Kavukcuoglu, Parallel WaveNet: Fast High-fidelity Speech Synthesis by Aaron van den Oord, Yazhe Li, Igor Babuschkin, Karen Simonyan, Oriol Vinyals, Koray Kavukcuoglu, George van den Driessche, Edward Lockhart, Luis C. Cobo, Florian Stimberg, Norman Casagrande, Dominik Grewe, Seb Noury, Sander Dieleman, Erich Elsen, Nal Kalchbrenner, Heiga Zen, Alex Graves, Helen King, Tom Walters, Dan Belov and Demis Hassabis and Efficient Neural Audio Synthesis by Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aaron van den Oord, Sander Dieleman and Koray Kavukcuoglu.

Audiovisual Description

Generating Natural Video Descriptions via Multimodal Processing by Qin Jin, Junwei Liang and Xiaozhu Lin, Multimodal Video Description by Vasili Ramanishka, Abir Das, Dong H. Park, Subhashini Venugopalan, Lisa A. Hendricks, Marcus Rohrbach and Kate Saenko, Describing Videos using Multi-modal Fusion by Qin Jin, Jia Chen, Shizhe Chen, Yifan Xiong and Alexander Hauptmann, Video Description Generation using Audio and Visual Cues by Qin Jin and Junwei Liang and Attention-based Multimodal Fusion for Video Description by Chiori Hori, Takaaki Hori, Teng-Yok Lee, Ziming Zhang, Bret Harsham, John R. Hershey, Tim K. Marks and Kazuhiko Sumi.

Audiovisual Generation

Deep Cross-modal Audio-visual Generation by Lele Chen, Sudhanshu Srivastava, Zhiyao Duan and Chenliang Xu and Visual to Sound: Generating Natural Sound for Videos in the Wild by Yipin Zhou, Zhaowen Wang, Chen Fang, Trung Bui and Tamara L. Berg.

Visuospatial Question Answering

Neural Scene Representation and Rendering by S. M. Ali Eslami, Danilo J. Rezende, Frederic Besse, Fabio Viola, Ari S. Morcos, Marta Garnelo, Avraham Ruderman, Andrei A. Rusu, Ivo Danihelka, Karol Gregor, David P. Reichert, Lars Buesing, Theophane Weber, Oriol Vinyals, Dan Rosenbaum, Neil Rabinowitz, Helen King, Chloe Hillier, Matt Botvinick, Daan Wierstra, Koray Kavukcuoglu and Demis Hassabis, Incorporating 3D Information into Visual Question Answering by Yue Qiu, Yutaka Satoh, Ryota Suzuki and Hirokatsu Kataoka and Multi-view Visual Question Answering with Active Viewpoint Selection by Yue Qiu, Yutaka Satoh, Ryota Suzuki, Kenji Iwata and Hirokatsu Kataoka.

Simulation Generation

Building Multimodal Simulations for Natural Language by James Pustejovsky and Nikhil Krishnaswamy, VoxSim: A Visual Platform for Modeling Motion Language by Nikhil Krishnaswamy and James Pustejovsky, Text to 3D Scene Generation with Rich Lexical Grounding by Angel X. Chang, Will Monroe, Manolis Savva, Christopher Potts and Christopher D. Manning and 3D Scene Creation Using Story-based Descriptions by Xin Zeng, Qasim Mehdi and Norman Gough.

Dialogue Systems

Visual Dialog by Abhishek Das, Satwik Kottur, Khushi Gupta, Avi Singh, Deshraj Yadav, José M. F. Moura, Devi Parikh and Dhruv Batra, Multi-turn Video Question Answering via Multi-stream Hierarchical Attention Context Network by Zhou Zhao, Xinghua Jiang, Deng Cai, Jun Xiao, Xiaofei He and Shiliang Pu, CLEVR-Dialog: A Diagnostic Dataset for Multi-round Reasoning in Visual Dialog by Satwik Kottur, José M. F. Moura, Devi Parikh, Dhruv Batra and Marcus Rohrbach, End-to-end Audio Visual Scene-aware Dialog Using Multimodal Attention-based Video Features by Chiori Hori, Huda Alamri, Jue Wang, Gordon Wichern, Takaaki Hori, Anoop Cherian, Tim K. Marks, Vincent Cartillier, Raphael G. Lopes, Abhishek Das, Irfan Essa, Dhruv Batra and Devi Parikh and End-to-end Optimization of Goal-driven and Visually Grounded Dialogue Systems by Florian Strub, Harm de Vries, Jeremie Mary, Bilal Piot, Aaron Courville and Olivier Pietquin.

Imagination, Mental Imagery and Meaning

Introduction

Semantic Memory as the Root of Imagination by Anna Abraham and Andreja Bubic and Handbook of Imagination and Mental Simulation edited by Keith D. Markman, William M. P. Klein and Julie A. Suhr.

Visuospatial Working Memory

The Nature of Visuospatial Representation within Working Memory by Colin Hamilton, Visuo-spatial Working Memory by Robert H. Logie and The Visuospatial Sketchpad for Mental Images: Testing the Multicomponent Model of Working Memory by Raymond Bruyer and Jean-Christophe Scailquin.

Semantic Working Memory

Notes on the Structure of Semantic Memory by Walter Kintsch, Semantic Memory and the Brain: Structure and Processes by Alex Martin and Linda L. Chao, On the Existence of Semantic Working Memory: Evidence for Direct Semantic Maintenance by Geeta Shivde and Michael C. Anderson, The Neurobiology of Semantic Memory by Jeffrey R. Binder and Rutvik H. Desai, Models of Semantic Memory by Michael N. Jones, Jon Willits, Simon Dennis and Michael Jones and The Neural and Computational Bases of Semantic Cognition by Matthew A. L. Ralph, Elizabeth Jefferies, Karalyn Patterson and Timothy T. Rogers.

Episodic Working Memory

Episodic and Semantic Memory by Endel Tulving, Cognitive Control and Episodic Memory by Anthony D. Wagner, The Episodic Buffer: A New Component of Working Memory? by Alan D. Baddeley and Binding in Visual Working Memory: The Role of the Episodic Buffer by Alan D. Baddeley, Richard J. Allen and Graham J. Hitch.

Automated Planning and Dialogue Systems

Automated Planning

Automated Planning: Theory and Practice by Malik Ghallab, Dana Nau and Paolo Traverso, Computational Models of Planning by Hector Geffner, Heuristic Search: Theory and Applications by Stefan Edelkamp and Stefan Schrödl, Implementing Fast Heuristic Search Code by Ethan A. Burns, Matthew Hatem, Michael J. Leighton and Wheeler Ruml, Accelerating Heuristic Search for AI Planning by You Xu, Can Cloud Computing be Used for Planning? An Initial Study by Qiang Lu, You Xu, Ruoyun Huang, Yixin Chen and Guoliang Chen, Iterative Resource Allocation for Memory Intensive Parallel Search Algorithms on Clouds, Grids, and Shared Clusters by Alex Fukunaga, Akihiro Kishimoto and Adi Botea and Planning in the Cloud: Massively Parallel Planning by Tommy Thompson and Dave Voorhis.

Dialogue Systems

Generating Dialogue Agents via Automated Planning by Adi Botea, Christian Muise, Shubham Agarwal, Oznur Alkan, Ondrej Bajgar, Elizabeth Daly, Akihiro Kishimoto, Luis Lastras, Radu Marinescu, Josef Ondrej, Pablo Pedemonte and Miroslav Vodolan and Planning for Goal-oriented Dialogue Systems by Christian Muise, Tathagata Chakraborti, Shubham Agarwal, Ondrej Bajgar, Arunima Chaudhary, Luis A. Lastras-Montano, Josef Ondrej, Miroslav Vodolan and Charlie Wiecha.

Intention and Plan Recognition

Analyzing Intention in Utterances by James F. Allen and C. Raymond Perrault, Planning and Understanding: A Computational Approach to Human Reasoning by Robert Wilensky, Attention, Intentions, and the Structure of Discourse by Barbara J. Grosz and Candace L. Sidner, Generalized Plan Recognition by Henry A. Kautz and James F. Allen, A Formal Theory of Plan Recognition by Henry A. Kautz, Plan Recognition in Natural Language Dialogue by Sandra Carberry, Plan Recognition Strategies for Language Understanding by Sandra Carberry and W. Alan Pope, Plan Recognition and Natural Language Understanding by Barbara Di Eugenio, Techniques for Plan Recognition by Sandra Carberry, A General Model for Online Probabilistic Plan Recognition by Hung H. Bui, On Natural Language Processing and Plan Recognition by Christopher W. Geib and Mark Steedman, Plan Recognition as Planning by Miquel Ramírez and Hector Geffner and A New Model of Plan Recognition by Robert P. Goldman, Christopher W. Geib and Christopher A. Miller.

Natural Language Generation

Natural Language Generation from Plans by Chris Mellish and Roger Evans, Natural Language Generation in Dialog Systems by Owen Rambow, Srinivas Bangalore and Marilyn Walker, Natural Language Generation as Planning Under Uncertainty for Spoken Dialogue Systems by Verena Rieser and Oliver Lemon, Towards Incremental Speech Generation in Dialogue Systems by Gabriel Skantze and Anna Hjalmarsson, Learning What to Say and How to Say It: Joint Optimisation of Spoken Dialogue Management and Natural Language Generation by Oliver Lemon and Natural Language Generation as Incremental Planning Under Uncertainty: Adaptive Information Presentation for Statistical Dialogue Systems by Verena Rieser, Oliver Lemon and Simon Keizer.

Multimedia Content Generation and Instructional Design

Plan-based Integration of Natural Language and Graphics Generation by Wolfgang Wahlster, Elisabeth André, Wolfgang Finkler, Hans-Jürgen Profitlich and Thomas Rist, The Design of Illustrated Documents as a Planning Task by Elisabeth André and Thomas Rist, Automatic Design of Multimodal Presentations by Wolfgang Wahlster, The Generation of Multimedia Presentations by Elisabeth André and Automating the Generation of Coordinated Multimedia Explanations by Steven K. Feiner and Kathleen R. McKeown.

Machine Teaching

Introduction

Machine Teaching: An Inverse Problem to Machine Learning and an Approach toward Optimal Education by Xiaojin Zhu, Machine Teaching: A New Paradigm for Building Machine Learning Systems by Patrice Y. Simard, Saleema Amershi, David M. Chickering, Alicia Edelman Pelton, Soroush Ghorashi, Christopher Meek, Gonzalo Ramos, Jina Suh, Johan Verwey, Mo Wang and John Wernsing, An Overview of Machine Teaching by Xiaojin Zhu, Adish Singla, Sandra Zilles and Anna N. Rafferty, Teacher Improves Learning by Selecting a Training Subset by Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang and Xiaojin Zhu, An Optimal Control Approach to Sequential Machine Teaching by Laurent Lessard, Xuezhou Zhang and Xiaojin Zhu, Iterative Machine Teaching by Weiyang Liu, Bo Dai, Ahmad Humayun, Charlene Tay, Chen Yu, Linda B. Smith, James M. Rehg and Le Song, Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners by Yuxin Chen, Adish Singla, Oisin M. Aodha, Pietro Perona and Yisong Yue, Towards Black-box Iterative Machine Teaching by Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James M. Rehg and Le Song and Teaching a Black-box Learner by Sanjoy Dasgupta, Daniel Hsu, Stefanos Poulis and Xiaojin Zhu.

Psychometric Artificial Intelligence

Natural Intelligence

Handbook of Intelligence edited by Robert J. Sternberg, The Cambridge Handbook of Intelligence edited by Robert J. Sternberg and Scott Barry Kaufman, The Neuroscience of Intelligence by Richard J. Haier, Intelligence and Cognitive Abilities as Competencies in Development by Damian P. Birney and Robert J. Sternberg and A Computational Analysis of General Intelligence Tests for Evaluating Cognitive Development by Fernando Martínez-Plumed, César Ferri, José Hernández-Orallo and María J. Ramírez-Quintana.

Artificial Intelligence

Universal Psychometrics: Measuring Cognitive Abilities in the Machine Kingdom by José Hernández-Orallo, David L. Dowe and M. Victoria Hernández-Lloreda, Can Machine Intelligence Be Measured in the Same Way as Human Intelligence? by Tarek Besold, José Hernández-Orallo and Ute Schmid, The Measure of All Minds: Evaluating Natural and Artificial Intelligence by José Hernández-Orallo, Historical Account of Computer Models Solving IQ Test Problems by Fernando Martınez-Plumed, José Hernández-Orallo, Ute Schmid, Michael Siebers and David L. Dowe, Computer Models Solving Intelligence Test Problems: Progress and Implications by José Hernández-Orallo, Fernando Martínez-Plumed, Ute Schmid, Michael Siebers and David L. Dowe, Verbal IQ of a Four-year Old Achieved by an AI System by Stellan Ohlsson, Robert H. Sloan, György Turán and Aaron Urasky, A Program for the Solution of a Class of Geometric-analogy Intelligence-test Questions by Thomas G. Evans, Solving Raven's IQ-tests: An AI and Cognitive Modeling Approach by Marco Ragni and Stefanie Neubert, Analyzing Raven's Intelligence Test: Cognitive Model, Demand, and Complexity by Marco Ragni and Stefanie Neubert, Measuring Abstract Reasoning in Neural Networks by Adam Santoro, Felix Hill, David Barrett, Ari Morcos and Timothy Lillicrap, DeepIQ: A Human-Inspired AI System for Solving IQ Test Problems by Jacek Mańdziuk and Adam Żychowski, Complexity in Analogy Tasks: An Analysis and Computational Model by Philip Stahl and Marco Ragni, Predicting Numbers: An AI Approach to Solving Number Series by Marco Ragni and Andreas Klein, An Anthropomorphic Method for Number Sequence Problems by Claes Strannegård, Mehrdad Amirghasemi and Simon Ulfsbäcker, Deep Neural Solver for Math Word Problems by Yan Wang, Xiaojiang Liu and Shuming Shi, Analysing Mathematical Reasoning Abilities of Neural Models by David Saxton, Edward Grefenstette, Felix Hill and Pushmeet Kohli, The Winograd Schema Challenge by Hector J. Levesque, Ernest Davis and Leora Morgenstern, Watson: Beyond Jeopardy! by David Ferrucci, Anthony Levas, Sugato Bagchi, David Gondek and Erik T. Mueller, A Study of the Knowledge Base Requirements for Passing an Elementary Science Test by Peter Clark, Philip Harrison and Niranjan Balasubramanian, MCTest: A Challenge Dataset for the Open-domain Machine Comprehension of Text by Matthew Richardson, Christopher J. C. Burges and Erin Renshaw, Recognizing Textual Entailment: Models and Applications by Ido Dagan, Dan Roth, Mark Sammons and Fabio M. Zanzotto, VQA: Visual Question Answering by Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C. Lawrence Zitnick and Devi Parikh, Towards AI-complete Question Answering: A Set of Prerequisite Toy Tasks by Jason Weston, Antoine Bordes, Sumit Chopra and Tomas Mikolov, Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions by Peter Clark, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Turney and Daniel Khashabi, Turing++ Questions: A Test for the Science of (Human) Intelligence by Tomaso Poggio and Ethan Meyers, My Computer Is an Honor Student — but How Intelligent Is It? Standardized Tests as a Measure of AI by Peter Clark and Oren Etzioni, A Dynamic Intelligence Test Framework for Evaluating AI Agents by Nader Chmait, Yuan-Fang Li, David L. Dowe and David G. Green, Using Thought-provoking Children's Questions to Drive Artificial Intelligence Research by Erik T. Mueller and Henry Minsky and How Well Do Machines Perform on IQ Tests: A Comparison Study on a Large-scale Dataset by Yusen Liu, Fangyuan He, Haodi Zhang, Guozheng Rao, Zhiyong Feng and Yi Zhou.

Artificial Wisdom

Introduction

Wisdom: Its Nature, Origins, and Development edited by Robert J. Sternberg, People Nominated as Wise: A Comparative Study of Wisdom-related Knowledge by Paul B. Baltes, Ursula M. Staudinger, Andreas Maercker and Jacqui Smith, Defining and Assessing Wisdom: A Review of the Literature by Katherine J. Bangen, Thomas W. Meeks and Dilip V. Jeste, What is Wisdom? Cross-cultural and Cross-disciplinary Syntheses by Roger Walsh and The Cambridge Handbook of Wisdom edited by Robert J. Sternberg and Judith Glück.

Conversational Search and Recommendation

A Theoretical Framework for Conversational Search by Filip Radlinski and Nick Craswell, Towards Conversational Recommender Systems by Konstantina Christakopoulou, Filip Radlinski and Katja Hofmann and Conversational Recommender System by Yueming Sun and Yi Zhang.

Anecdotes

Anecdote Recognition and Recommendation by Wei Song, Ruiji Fu, Lizhen Liu, Hanshi Wang and Ting Liu.

Proverbs

Proverbs: A Handbook by Wolfgang Mieder, A Proverb in Mind: The Cognitive Science of Proverbial Wit and Wisdom by Richard P. Honeck, Comprehension and the Interpretation of Proverbs by Susan Kemper and Introduction to Paremiology: A Comprehensive Guide to Proverb Studies edited by Hrisztalina Hrisztova-Gotthardt and Melita Aleksa Varga.

Quotations

Words to Live By: Scholarly Quotations as Proverbial Theory by Corey Anton, Learning to Recommend Quotes for Writing by Jiwei Tan, Xiaojun Wan and Jianguo Xiao and Quote Recommendation for Dialogs and Writings by Yeonchan Ahn, Hanbit Lee, Heesik Jeon, Seungdo Ha and Sang-goo Lee.

Lyrics

Music Search Engines: Specifications and Challenges by Alexandros Nanopoulos, Dimitrios Rafailidis, Maria M. Ruxanda and Yannis Manolopoulos, Music Recommender Systems by Markus Schedl, Peter Knees, Brian McFee, Dmitry Bogdanov and Marius Kaminskas and Current Challenges and Visions in Music Recommender Systems Research by Markus Schedl, Hamed Zamani, Ching-Wei Chen, Yashar Deldjoo and Mehdi Elahi.

Poetry

An Introduction to Poetry by X. J. Kennedy and Dana Gioia and Cognitive Poetics: An Introduction by Peter Stockwell.

Narrative

Interpretation, Allegory, and Allegoresis by Peter Berek, Allegory and Allegoresis, Rhetoric and Hermeneutics by Rita Copeland and Stephen Melville and A Survey of Book Recommender Systems by Haifa Alharthi, Diana Inkpen and Stan Szpakowicz.

Allusion

What is an Allusion? by William Irwin, The Poetics of Literary Allusion by Ziva Ben-Porat, Intertextuality, Allusion, and Quotation: An International Bibliography of Criticial Studies by Udo J. Hebel, Beyond Literal Meanings: The Psychology of Allusion by Sam Glucksberg and The Aesthetics of Allusion by William T. Irwin.

Humor

Computational Humor by Kim Binsted, Benjamin Bergen, Seana Coulson, Anton Nijholt, Oliviero Stock, Carlo Strapparava, Graeme Ritchie, Ruli Manurung, Helen Pain, Annalu Waller and Dave O'Mara and Joke Retrieval: Recognizing the Same Joke Told Differently by Lisa Friedland and James Allan.

Artificial Intelligence and Music

Introduction

Psychology of Music edited by Diana Deutsch, Oxford Handbook of Music Psychology edited by Susan Hallam, Ian Cross and Michael Thaut, Music, Language, and the Brain by Aniruddh D. Patel, Understanding Music with AI: Perspectives on Music Cognition edited by Mira Balaban, Kemal Ebcioğlu and Otto Laske, Readings in Music and Artificial Intelligence edited by Eduardo R. Miranda and Music, Mind and Machine: Studies in Computer Music, Music Cognition and Artificial Intelligence by Peter Desain and Henkjan Honing.

Aesthetics

Aesthetics: An Introduction to the Philosophy of Art by Anne Sheppard, Philosophy of the Arts: An Introduction to Aesthetics by Gordon Graham, Aesthetics and Cognitive Science by Gregory Currie, Aesthetics and Cognitive Science by Dustin Stokes and The Aesthetics of Music by Roger Scruton.

Emotion

Emotion and Meaning in Music by Leonard B. Meyer, Emotional Expression in Music Performance: Between the Performer's Intention and the Listener's Experience by Alf Gabrielsson and Patrik N. Juslin, The Effects of Different Types of Music on Mood, Tension, and Mental Clarity by Rollin McCraty, Bob Barrios-Choplin, Michael Atkinson and Dana Tomasino, Emotion Induction through Music: A Review of the Musical Mood Induction Procedure by Daniel Västfjäll, From Everyday Emotions to Aesthetic Emotions: Towards a Unified Theory of Musical Emotions by Patrik N. Juslin, Which Emotions Can be Induced by Music? What are the Underlying Mechanisms? And How Can We Measure Them? by Klaus R. Scherer, Emotional Responses to Music: The Need to Consider Underlying Mechanisms by Patrik N. Juslin and Daniel Västfjäll, Combining Music with Thought to Change Mood by Eric Eich, Joycelin T. W. Ng, Dawn Macaulay, Alexandra D. Percy and Irina Grebneva, Modeling Listeners' Emotional Response to Music by Tuomas Eerola, The Functions of Music for Affect Regulation by Annelies van Goethem and John Sloboda, Emotion Regulation through Listening to Music in Everyday Situations by Myriam V. Thoma, Stefan Ryf, Changiz Mohiyeddini, Ulrike Ehlert and Urs M. Nater and Personalized Affective Music Player by Joris H. Janssen, Egon L. van den Broek and Joyce H. D. M. Westerink.

Athletic Performance

The Effects of Music on Athletic Performance by Haluk Koç and Turchıan Curtseıt, The Effect of Music on Athletic Cardio-respiratory Responses and Perceived Exertion Rate during Incremental Exercise by Hamed Barzegar, Rahman Soori, Ali Akbarnejad and Elham Vosadi, Effect of Music Tempo on Exercise Performance and Heart Rate among Young Adults by Avinash E. Thakare, Ranjeeta Mehrotra and Ayushi Singh, The Effect of Music Playlist Tempo on Self-paced Running, Mood, and Attentional Focus Tendencies by Kristopher Bly, Psychophysical and Ergogenic Effects of Synchronous Music during Treadmill Walking by Costas I. Karageorghis, Denis A. Mouzourides, David-Lee Priest, Tariq A. Sasso, Daley J. Morrish and Carolyn L. Walley, Effects of Motivational Music on a 1.5 Mile Running Time Trial by Jamie C. Aweau, A Motivational Music and Video Intervention Improves High-intensity Exercise Performance by Martin J. Barwood, Neil J. V. Weston, Richard Thelwell and Jennifer Page, Applying Music in Exercise and Sport by Costas I. Karageorghis and A Personalized Music System for Motivation in Sport Performance by Gertjan Wijnalda, Steffen Pauws, Fabio Vignoli and Heiner Stuckenschmidt.

Productivity

The Effect of Music Listening on Work Performance by Teresa Lesiuk, The Effect of Preferred Music on Mood and Performance in a High-cognitive Demand Occupation by Teresa Lesiuk, Background Music and Cognitive Performance by Leslie A. Angel, Donald J. Polzella and Greg C. Elvers and The Impact of Background Music on Adult Listeners: A Meta-analysis by Juliane Kämpfe, Peter Sedlmeier and Frank Renkewitz.

Creativity

Effects of Mood States on Creativity by Franck Zenasni and Todd Lubart and The Effects of Musical Mood Induction on Creativity by Jill E. Adaman and Paul H. Blaney.

Flow

Optimal Experience: Psychological Studies of Flow in Consciousness edited by Mihaly Csikszentmihalyi and Isabella S. Csikszentmihalyi and Mindfulness, Attention, and Flow during Music Listening: An Empirical Investigation by Frank M. Diaz.

Studying and Concentration

The Perceived Impact of Playing Music while Studying: Age and Cultural Differences by Anastasia Kotsopoulou and Susan Hallam, The Effects of Different Types of Music on Mood, Tension, and Mental Clarity by Rollin McCraty, Bob Barrios-Choplin, Michael Atkinson and Dana Tomasino, Background Music and Cognitive Performance by Leslie A. Angel, Donald J. Polzella and Greg C. Elvers and The Impact of Background Music on Adult Listeners: A Meta-analysis by Juliane Kämpfe, Peter Sedlmeier and Frank Renkewitz.

Problem Solving

Human Problem Solving by Allen Newell and Herbert A. Simon, Effect of Music on Cooperative Problem Solving in Children by Sanford L. Chertock and Relationship between Musical Accompaniment and Learning Style in Problem Solving by Linda Burton.

Intelligent Tutoring Systems

Affect-aware Tutors: Recognising and Responding to Student Affect by Beverly P. Woolf, Winslow Burleson, Ivon Arroyo, Toby Dragon, David Cooper and Rosalind Picard, Multimodal Affect Recognition in Intelligent Tutoring Systems by Ntombikayise Banda and Peter Robinson and Affect and Cognitive Processes in Educational Contexts by Klaus Fiedler and Susanne Beier.

Affective Computing

Affective Computing by Rosalind W. Picard, Recognition and Simulation of Emotions by Christian Kleine-Cosack, Recognition of Vocal Emotions from Acoustic Profile by Krishna Asawa, Vikrant Verma and Ankit Agrawal, Multimodal Emotion Recognition for Human-computer Interaction: A Survey by Michele Mukeshimana, Xiaojuan Ban, Nelson Karani and Ruoyi Liu, Mind-reading Machines: Automated Inference of Complex Mental States by Rana A. El Kaliouby and Empirically Building and Evaluating a Probabilistic Model of User Affect by Cristina Conati and Heather Maclaren.

Computational Representation of Music

A Guide to Musical Analysis by Nicholas Cook, A System for the Analysis of Musical Data by Stuart Pullinger, Music Representation: Issues, Techniques, and Systems by Roger B. Dannenberg, The Music Structures Approach to Knowledge Representation for Music Processing by Mira Balaban, A Generative Theory of Tonal Music by Fred Lerdahl and Ray S. Jackendoff, Features for Audio and Music Classification by Martin McKinney and Jeroen Breebaart, The Music Genome Project by Michael Castelluccio, Moving beyond Feature Design: Deep Architectures and Automatic Feature Learning in Music Informatics by Eric J. Humphrey, Juan Pablo Bello and Yann LeCun, Improved Music Feature Learning with Deep Neural Networks by Siddharth Sigtia and Simon Dixon and What is Musical Prosody? by Caroline Palmer and Sean Hutchins.

Music Understanding

The Origins of Music Perception and Cognition: A Developmental Perspective by Sandra Trehub, E. Glenn Schellenberg and David S. Hill, Thinking in Sound: The Cognitive Psychology of Human Audition edited by Stephen McAdams and Emmanuel Bigand, Exploring the Functional Neuroanatomy of Music Performance, Perception, and Comprehension by Lawrence M. Parsons, Perception and Cognition of Music edited by Irène Deliège and John A. Sloboda, Towards a Neural Basis of Music Perception by Stefan Koelsch and Walter A. Siebel, Music Cognition and the Cognitive Sciences by Marcus Pearce and Martin Rohrmeier and Understanding Music with AI: Perspectives on Music Cognition edited by Mira Balaban, Kemal Ebcioğlu and Otto Laske.

Music Generation

Algorithmic Composition: Paradigms of Automated Music Generation by Gerhard Nierhaus, Algorithmic Composition: Computational Thinking in Music by Michael Edwards, AI Methods in Algorithmic Composition: A Comprehensive Survey by Jose D. Fernández and Francisco Vico and Deep Learning Techniques for Music Generation - A Survey by Jean-Pierre Briot, Gaëtan Hadjeres and François Pachet.

Recommender Systems

Music Recommender Systems by Markus Schedl, Peter Knees, Brian McFee, Dmitry Bogdanov and Marius Kaminskas, Current Challenges and Visions in Music Recommender Systems Research by Markus Schedl, Hamed Zamani, Ching-Wei Chen, Yashar Deldjoo and Mehdi Elahi and A Comparative Study of Music Recommendation Systems by Ashish Patel and Rajesh Wadhvani.

Playlist Generation

"More of an Art than a Science": Supporting the Creation of Playlists and Mixes by Sally Jo Cunningham, David Bainbridge and Annette Falconer, A Discussion of Musical Features for Automatic Music Playlist Generation using Affective Technologies by Darryl Griffiths, Stuart Cunningham and Jonathan Weinel, Towards a Personal Automatic Music Playlist Generation Algorithm: The Need for Contextual Information by Gordon Reynolds, Dan Barry, Ted Burke and Eugene Coyle and Automated Generation of Music Playlists: Survey and Experiments by Geoffray Bonnin and Dietmar Jannach.