A few publications of Jonathan Gratch (Complete list here or GoogleScholar)

   Emotion

Rapport

Virtual Humans

Intelligent Agents

   Adaptive Problem Solving

Emotion and Social Modeling

Rafa Calvo, Sidney D'Mello, Jonathan Gratch and Arvid Kappas (Eds). Handbook of Affective Computing. Oxford University Press. 2015

Gale Lucas, Jonathan Gratch, Lin Cheng and Stacy Marsella. When the going gets tough: Grit Predicts costly perseverance. Journal of Research in Personality v59. 2015 pp 15-22

Yuqiong Wang, Gale Lucas, Peter Khooshabeh, Celso De Melo and Jonathan Gratch. 'Effects of Emotional Expressions on Persuasion. Social Influence 10(4). 2015 pp. 236-249

Stacy Marsella and Jonathan Gratch. Computationally Modeling Human Emotion. Communications of the ACM, Vol. 57 No. 12, Pages 56-67

Celso de Melo, Jonathan Gratch and Peter Carnevale. The importance of cognition and affect for artificially intelligent decision makers. 28th AAAI Conference on Artificial Intelligence. Québec City, Canada 2014

Jonathan Gratch and Stacy Marsella (Eds.). Social Emotions in Nature and Artifact. Oxford University Press, 2013

Celso de Melo, Peter Carnevale, Stephen Read and Jonathan Gratch. Reading people’s minds from emotion expressions in interdependent decision making.  Journal of Personality and Social Psychology, 106(1), 2014, pp. 73-88

Rainer Reisenzein, Eva Hudlicka, Mehdi Dastani, Jonathan Gratch, Koen Hindriks, Emiliano Lorini, and John-Jules Meyer. Computational Modeling of Emotion: Towards Improving the Inter- and Intradisciplinary Exchange. IEEE Transactions on Affective Computing, 4(3), 2013, pp. 246-266

Wenji Mao and Jonathan Gratch. Modeling Social Causality and Responsibility Judgment in Multi-Agent Interactions. Journal of Artificial Intelligence Research. Vol 44. 2012. pp 223-273.

Jonathan Gratch, Lin Cheng, Stacy Marsella and Jill Boberg. Felt emotion and social context determine the intensity of smiles in a competitive video game. 10th IEEE International Conference on Automatic Face and Gesture Recognition. Shanghai, China, April 2013

Stacy Marsella, Jonathan Gratch and Paolo Petta. Computational Models of Emotion. In in Scherer, K.R., Bänziger, T., & Roesch, E. (Eds.) A blueprint for a affective computing: A sourcebook and manual. Oxford: Oxford University Press, 2010

Stacy Marsella and Jonathan Gratch, EMA: A Process Model of Appraisal Dynamics. Journal of Cognitive Systems Research, vol 10(1), 2009, pp 70-90

Jonathan Gratch and Stacy Marsella, "A Domain-independent framework for modeling emotion, " Journal of Cognitive Systems Research, Volume 5, Issue 4, 2004, pp. 269-306

Rapport and Social Effects

Gale Lucas, Jonathan Gratch, Aisha King and Louis-Philippe Morency. It's Only a Computer: Virtual Humans Increase Willingness to Disclose. Journal of Computers in Human Behavior. v37. 2014. pp. 94-100

Jana Appel, Astrid Marieke von der Pütten, Nicole C. Krämer and Jonathan Gratch. Does humanity matter? Analyzing the importance of social cues and perceived agency of a computer system for the emergence of social reactions during human-computer interaction. Advances in Human-Computer Interaction. 13, 2012

Lixing Huang, Louis-Philippe Morency, Jonathan Gratch. Learning Backchannel Prediction Model from Parasocial Consensus Sampling: A Subjective Evaluation. 10th International Conference on Intelligent Virtual Agents, Philadelphia, PA. 2010.

Lixing Huang, Louis-Philippe Morency, Jonathan Gratch. Parasocial Consensus Sampling: Combining Multiple Perspectives to Learn Virtual Human Behavior. 9th International Conference on Autonomous Agents and Multiagent Systems. Toronto, Canada, 2010.

Jonathan Gratch, Ning Wang, Jillian Gerten, Edward Fast and Robin Duffy. Creating Rapport with Virtual Agents. 7th International Conference on Intelligent Virtual Agents, Paris, France 2007

Gratch, J., Wang, N., Okhmatovskaia, A., Lamothe, F., Morales, M and Louis-Philippe Morency. Can virtual humans be more engaging than real ones? 12th International Conference on Human-Computer Interaction, Beijing, China 2007

Virtual Humans

Jonathan Gratch, David DeVault, Gale Lucas, Stacy Marsella. Negotiation as a Challenge Problem for Virtual Humans. 15th International Conference on Intelligent Virtual Agents. Delft, The Netherlands. 2015.

Zahra Nazari, Gale Lucas and Jonathan Gratch. Opponent Modeling for Virtual Human Negotiators. 15th International Conference on Intelligent Virtual Agents. Delft, The Netherlands. 2015.

David DeVault, Ron Artstein, Grace Benn, Teresa Dey, Alesia Egan, Ed Fast, Kallirroi Georgila, Jonathan Gratch, Arno Hartholt, Margaux Lhommet, et al. SimSensei: A Virtual Human Interviewer for Healthcare Decision Support. 13th International Conference on Autonomous Agents and Multiagent Systems. Paris, France 2014

 

Intelligent Agents

Youngjun Kim, Randall Hill, and Jonathan Gratch, "How long can you look away from a target," Proceedings of the 9th Conference on Computer Generated Forces and Behavioral Representation, May 2000

Randall Hill, Jonathan Gratch and Paul Rosenbloom, "Flexible group behavior: lessons learned building virtual commanders," Procedings of the 9th Conference on Computer Generated Forces and Behavioral Representation, May 2000

Jonathan Gratch and Randall W. Hill, Jr., "Continuous Planning and Collaboration for Command and Control in Joint Synthetic Battlespaces," in Proceedings of the Eighth Conference on Computer Generated Forces and Behavioral Representation, 1999 (postscript)

Randall Hill, Johnny Chen, Jonathan Gratch, Paul Rosenbloom, Milind Tambe, "Intelligent Agents for the Synthetic Battlefield," in "Joint proceedings of the Fourteenth National Conference on Artificial Intellignece and the Ninth Conference on Innovative Applications of Artificial Intelligence (AAAI/IAAI97), Providence, RI, 1997, pp. 1006-1012 (postscript)

Jonathan Gratch and Randy Hill, "Continuous Planning and Collaboration for Command and Control in Joint Synthetic Battlespaces," "Proceedings of the 8th Conference on Computer Generated Forces and Behavioral Representation, Orlando, FL, 1999

Jonathan Gratch, Stacy Marsella, Randy Hill and LTC George Stone, "Deriving Priority Infomration Requirements for Synthetic Command Entities," "Proceedings of the 8th Conference on Computer Generated Forces and Behavioral Representation, Orlando, FL, 1999

Randall Hill, Johnny Chen, Jonathan Gratch, Paul Rosenbloom, Milind Tambe, "Soar-RWA: Planning, teamwork, and intelligent behavior for synthetic rotary wing aircraft," in "Proceedings of the Seventh Conference on Computer Generated Forces and Behavioral Representation, Orlando, FL, 1998 (postscript)

Jonathan Gratch, "Task-decomposition Planning for Command Decision Making," "Proceedings of the Sixth Conference on Computer Generated Forces and Behavioral Representation, Orlando, FL, 1996, pp. 37-45

Adaptive Problem Solving / Machine Learning

Jonathan Gratch, "On Efficient Approaches to the Utlity Problem in Adaptive Problem Solving," Ph.D. Thesis, Report No. UIUCDCS-R-95-1916, 1995 (PDF)

Jonathan Gratch and Gerald DeJong, "A Decision-theoretic Approach to Adaptive Problem Solving," "Artificial Intelligence, (88) 1-2, 1996, pp. 101-142 (postscript)

Jonathan Gratch and Steve Chien, "Adaptive Problem-solving for Large-scale Scheduling Problems: A Case Study," "Journal of Artificial Intelligence Research 4, 1996, pp. 365-396

Jonathan Gratch, "Sequential Inductive Learning," "Proceedings of Thirteenth National Conference on Artificial Intelligence (AAAI96), 1996, pp. 778-786

Steve Chien, Jonathan Gratch, and Michael Burl, "On the Efficient Allocation of Resources for Hypothesis Evaluation: A Statistical Approach," " IEEE Transaction on Pattern Analysis and Machine Learning (PAMI), 17(4), 1995, pp. 652-665

Jonathan Gratch, Steve Chien, and Gerald DeJong, "Improving Learning Performance Through Rational Resource Allocation," "Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI94), Seattle, WA, 1994, pp. 576-581

Jonathan Gratch, Steve Chien, and Gerald DeJong, "Learning Search Control Knowledge for the Deep Space Network Scheduling Problem," "Proceedings of the Tenth International Machine Learning Conference (ML93), Amherst, MA, 1993, pp. 135-142 (postscript)

Jonathan Gratch and Gerald DeJong, "COMPOSER: A Probabilistic Solution to the Utility Problem in Speed-up Learning," "Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI92), San Jose, CA, 1992, pp. 235-240