Title

Refining Human Behavior Models In A Context-Based Architecture

Abstract

This paper describes an investigation into the refinement of context-based human behavior models through the use of experiential learning. Specifically, a tactical agent was endowed with a context-based control model developed through other means and tasked with a mission in a simulation. This simulation-based mission was employed to expose the agent to situations possibly not considered in the model's original construction. Reinforcement learning was used to evaluate and refine the performance of this agent to improve its effectiveness and generality.

Publication Date

7-24-2006

Publication Title

FLAIRS 2006 - Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference

Volume

2006

Number of Pages

649-650

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

33746082447 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33746082447

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