Evaluating Social Causality and Responsibility Models: An Initial Report
Abstract
Intelligent virtual agents are typically embedded in a social environment and must reason about social cause and effect. Social causal reasoning is qualitatively different from physical causal reasoning that underlies most current intelligent systems. Besides physical causality, the assessments of social cause emphasize epistemic variables including intentions, foreknowledge and perceived coercion. Modeling the process and inferences of social causality can enrich believability and cognitive capabilities of social intelligent agents. In this report, we present a general computational model of social causality and responsibility, and empirical results of a preliminary evaluation of the model in comparison with several other approaches.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2005
- Accession Number
- ADA459213
Entities
People
- Jonathan Gratch
- Wenji Mao
Organizations
- University of Southern California