An Agent-Based System for Simulating Dynamic Choice-Sets

Abstract

Contributing to the recent interest in the dynamics of activity-travel patterns, this paper discusses a framework for the dynamic formation of location choice-sets. It is based on the concepts of aspiration, activation and expected utility. Based on principles of Bayesian learning, reinforcement learning and social comparison theories, the framework specifies functions for experience-based learning, extended and integrated with social learning.