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.

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.

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

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.

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.

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: 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 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: 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.

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.

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 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.

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: 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.

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.

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.

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.

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.

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

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.

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.

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.

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

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.

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.

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.

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: 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 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.

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.

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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

"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.

An Essay on the Psychology of Invention in the Mathematical Field by Jacques Hadamard, The Psychology of Advanced Mathematical Thinking by David Tall, What is Mathematical Thinking by Robert J. Sternberg, Mathematical Thinking and Learning by Herbert P. Ginsburg, Joanna Cannon, Janet Eisenband and Sandra Pappas, Mathematical Problem Solving by Alan H. Schoenfeld, How to Solve It: A New Aspect of Mathematical Method by George Polya, The Computer Modelling of Mathematical Reasoning by Alan Bundy, Modelling the Way Mathematics is Actually Done by Joseph Corneli, Ursula Martin, Dave Murray-Rust, Alison Pease, Raymond Puzio and Gabriela R. Nesin and Proof Assistants: History, Ideas and Future by Herman Geuvers.

Deep Neural Solver for Math Word Problems by Yan Wang, Xiaojiang Liu and Shuming Shi, Deep Learning for Symbolic Mathematics by Guillaume Lample and François Charton and Analysing Mathematical Reasoning Abilities of Neural Models by David Saxton, Edward Grefenstette, Felix Hill and Pushmeet Kohli.

Learning from Previous Proof Experience: A Survey by Jörg Denzinger, Matthias Fuchs, Christoph Goller and Stephan Schulz, Automatic Acquisition of Search Control Knowledge from Multiple Proof Attempts by Jörg Denzinger and Stephan Schulz, Reinforcement Learning of Theorem Proving by Cezary Kaliszyk, Josef Urban, Henryk Michalewski and Miroslav Olšák, Learning Heuristics for Automated Reasoning through Deep Reinforcement Learning by Gil Lederman, Markus N. Rabe and Sanjit A. Seshia, DeepMath - Deep Sequence Models for Premise Selection by Geoffrey Irving, Christian Szegedy, Alexander A. Alemi, Niklas Een, François Chollet and Josef Urban, Deep Network Guided Proof Search by Sarah M. Loos, Geoffrey Irving, Christian Szegedy and Cezary Kaliszyk, Learning to Prove with Tactics by Thibault Gauthier, Cezary Kaliszyk, Josef Urban, Ramana Kumar and Michael Norrish and Hierarchical Invention of Theorem Proving Strategies by Jan Jakubův and Josef Urban.

Peirce's Theory of Abduction by Arthur W. Burks, The Inference to the Best Explanation by Gilbert H. Harman, On the Mechanization of Abductive Logic by Harry E. Pople, The Computational Complexity of Abduction by Tom Bylander, Dean Allemang, Michael C. Tanner and John R. Josephson and Abductive Inference: Computation, Philosophy, Technology edited by John R. Josephson and Susan G. Josephson.

Incremental Interpretation by Fernando C. N. Pereira and Martha E. Pollack, Incremental Interpretation edited by David Milward and Patrick Sturt, What is Incremental Interpretation by Nick Chater, Martin Pickering and David Milward, Computational Models of Incremental Semantic Interpretation by Nicholas J. Haddock, The Information-processing Difficulty of Incremental Parsing by John Hale, Incremental Interpretation and Prediction of Utterance Meaning for Interactive Dialogue by David DeVault, Kenji Sagae and David Traum and Incremental Dialogue Understanding and Feedback for Multiparty, Multimodal Conversation by David Traum, David DeVault, Jina Lee, Zhiyang Wang and Stacy Marsella.

Rationale and Methods for Abductive Reasoning in Natural-language Interpretation by Mark E. Stickel, Interpretation as Abduction by Jerry R. Hobbs, Mark E. Stickel, Douglas E. Appelt and Paul Martin, Abductive Reasoning in Peirce's and Davidson's Account of Interpretation by Uwe Wirth, Layered Abduction for Speech Recognition from Articulation by Richard K. Fox, Abduction in Natural Language Understanding by Jerry R. Hobbs, Abductive Speech Act Recognition by Elizabeth A. Hinhelman, Abduction for Discourse Interpretation: A Probabilistic Framework by Ekaterina Ovchinnikova, Andrew Gordon and Jerry R. Hobbs and Abduction, Belief and Context in Dialogue: Studies in Computational Pragmatics edited by Harry Bunt and William Black.

How People Explain Behavior: A New Theoretical Framework by Bertram F. Malle, Understanding Social Interactions using Incremental Abductive Inference by Ben Meadows and Miranda Emery and An Abductive Approach to Understanding Social Interactions by Ben Meadows, Patrick Langley and Miranda Emery.

Conflicting Readings: Variety and Validity in Interpretation by Paul B. Armstrong, Arguing over Intentions by Paisley Livingston, Interpretation and Justification by David Novitz, Validity in Interpretation by Eric D. Hirsch, Validity in Interpretation and the Literary Institution by Ken M. Newton and Argumentation and the Social Grounds of Knowledge by Charles A. Willard.

Observational Learning by Albert Bandura, Social Learning Theory by Albert Bandura and Richard H. Walters and Perspectives on Observational Learning in Animals by Thomas R. Zentall.

Robot Learning from Human Teachers by Sonia Chernova and Andrea L. Thomaz, Robot Learning from Demonstration by Christopher G. Atkeson and Stefan Schaal, A Survey of Robot Learning from Demonstration by Brenna D. Argall, Sonia Chernova, Manuela Veloso and Brett Browning, Robot Programming by Demonstration by Aude Billard, Sylvain Calinon, Ruediger Dillmann and Stefan Schaal, Programming by Demonstration: A Taxonomy of Current Relevant Methods to Teach and Describe New Skills to Robots by Jordi Bautista-Ballester, Jaume Vergés-Llahí and Domenec Puig and Learning Procedural Knowledge through Observation by Michael van Lent and John E. Laird.

Interactive Task Learning by John E. Laird, Kevin A. Gluck, John Anderson, Kenneth D. Forbus, Odest C. Jenkins, Christian Lebiere, Dario Salvucci, Matthias Scheutz, Andrea Thomaz, Greg Trafton, Robert E. Wray, Shiwali Mohan and James R. Kirk and Interactive Task Learning: Humans, Robots, and Agents Acquiring New Tasks through Natural Interactions edited by Kevin A. Gluck and John E. Laird.

Multi-agent Reinforcement Learning: Independent vs. Cooperative Agents by Ming Tan, The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems by Caroline Claus and Craig Boutilier, Implicit Imitation in Multiagent Reinforcement Learning by Bob Price and Craig Boutilier, Observational Learning by Reinforcement Learning by Diana Borsa, Nicolas Heess, Bilal Piot, Siqi Liu, Leonard Hasenclever, Remi Munos and Olivier Pietquin, Learning in Multi-agent Systems by Eduardo Alonso, Mark D'inverno, Daniel Kudenko, Michael Luck and Jason Noble and Learning to Teach in Cooperative Multiagent Reinforcement Learning by Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell and Jonathan P. How.