Adaptive Modeling and Planning for Reactive Agents

Mykel J. Kochenderfer

This research is concerned with problems where an agent is situated in a stochastic world without prior knowledge of the world’s dynamics. The agent must act in such a way so as to maximize its expected discounted reward over time. The state and action spaces are extremely large or infinite, and control decisions are made in continuous time. The objective of this research is to create a system capable of generating competent behavior in real time.

Subjects: 12.1 Reinforcement Learning; 15.4 Reactive Control

Submitted: Apr 4, 2005


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