Evaluating a computational model of social causality and responsibility

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. Categories and Subject Descriptors I.2 [Computing Methodologies]: Artificial Intelligence; J.4 [Computer Applications]: Social and Behavioral Sciences General Terms Algorithms, Experimentation Keywords Intelligent Agents, Cognitive Modeling, Causality, Commonsense Reasoning

• Type: Conference
• Year: 2006
• Where: ATAL
• Authors: Wenji Mao, Jonathan Gratch
• Keywords: ATAL 2006, Causal Reasoning, Intelligent Agents, Social