Research and Development



Please feel free to browse our newest research articles:

(1) Alignment and Contextual Action Selection discusses designing, training, operating, and evaluating artificial-intelligence systems which contextually learn, respond to stimuli, and select actions while maintaining internal representations of stories, computer simulations, or real-world environments.

(2) Multi-agent Question-answering Systems broaches that agents representing ideological stances, positions, perspectives, or schools of thought can serve in multi-agent systems which can generate encyclopedic answers to end-users' complex questions.

(3) The Contextual Recommendation of Advice and Wisdom proposes a new multidisciplinary challenge to design and build artificial intelligence systems capable of contextually recommending advice and wisdom in the forms of allegories, anecdotes, aphorisms, apologues, fables, folklore, historical analogues, jokes, literature, lyrics, parables, poems, proverbs, quotations, stories, and witticisms.

(4) Adaptive Instructional Systems, Interactive Storytelling and Character Education responds to calls for more rigorous approaches for character education programs and their evaluation. Interactive stories (e.g., guided play, role-playing games, the case method, decision games, simulations, literature and literary discussions, story-based items, digital gamebooks, interactive films, and serious games) can be utilized as classroom and homework exercises for character education and social and emotional learning programs. Adaptive instructional systems can select and sequence these exercises for learners at scale, providing learners with individualized and optimized instruction and assessment.


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