Simulating belief systems of autonomous agents
Abstract
Autonomous agents in computer simulations do not have the usual mechanisms to acquire information as do their
human counterparts. In many such simulations, it is not desirable that the agent have access to complete and correct
information about its environment. We examine how imperfection in available information may be simulated in the
case of autonomous agents. We determine probabilistically what the agent may detect, through hypothetical sensors,
in a given situation. These detections are combined with the agent's knowledge base to infer observations and
beliefs. Inherent in this task is a degree of uncertainty in choosing the most appropriate observation or belief. We
describe and compare two approaches -a numerical approach and one based on defeasible logic -for simulating an
appropriate belief in light of conflicting detection values at a given point in time. We discuss the application of this
technique to autonomous forces in combat simulation systems.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Collections
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