Representing Social Agents, Actions, and Knowledge States at Separate Levels of Explicitness

Abstract

This dissertation first sketches a framework integrating various processes that have been proposed to account for the human capacity for action perception and analysis. The framework is then applied to interpreting two sets of experiments. In the first set I investigate how automatic simulation processes function in predicting reaches from perceiving gazes. In the second set I test the costs versus benefits to one's learning from the deliberate reasoning about a social agent's knowledge states, and the consequent social highlighting behaviors one engages in, when demonstrating an action. Taken together, these studies suggest roles as well as limitations for automatic simulation and deliberate inferential reasoning in action perception and understanding.