A computational theory of grounding in natural language conversation
A computational theory of grounding in natural language conversation
Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
Machine Learning - Special issue on applications of machine learning and the knowledge discovery process
Reasoning with Cause and Effect
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Causes and Explanations: A Structural-Model Approach: Part 1: Causes
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
The kappa statistic: a second look
Computational Linguistics
Social Judgment in Multiagent Interactions
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Social causality and responsibility: modeling and evaluation
Lecture Notes in Computer Science
Responsibility and blame: a structural-model approach
Journal of Artificial Intelligence Research
Towards a validated model of "emotional intelligence"
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
ZiF'06 Proceedings of the Embodied communication in humans and machines, 2nd ZiF research group international conference on Modeling communication with robots and virtual humans
EMA: A process model of appraisal dynamics
Cognitive Systems Research
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Intelligent agents are typically situated in a social environment and must reason about social cause and effect. Such reasoning is qualitatively different from physical causal reasoning that underlies most intelligent systems. Modeling social causal reasoning can enrich the capabilities of multi-agent systems and intelligent user interfaces. In this paper, we empirically evaluate a computational model of social causality and responsibility against human social judgments. Results from our experimental studies show that in general, the model's predictions of internal variables and inference process are consistent with human responses, though they also suggest some possible refinement to the computational model.