Date of Award:

5-2011

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Plants, Soils, and Climate

Advisor/Chair:

Dr. Christopher A. Call

Abstract

A number of technical approaches had to be employed within the planner, namely, 1) translating expected reward into a probability of goal satisfaction criterion, 2) monitoring belief states with a Rao-Blackwellized particle, and 3) employing Rao-Blackwellized particles in the McLUG probabilistic conformant planning graph heuristic. POND-Hindsight is an action selection mechanism that evaluates each possible action by generating a number of lookahead samples (up to a xed horizon) that greedily select actions based on their heuristic value and samples the actions' observation; the average goal satisfaction probability of the end horizon belief states is used as the value of each action.

Comments

This work was made publicly available electronically on September 29, 2011.

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