Author

John Phelps

Date of Award

2003

Level of Access

Open-Access Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

Advisor

Thomas Wahner

Second Committee Member

Paul Bauschatz

Third Committee Member

James Fastook

Abstract

An effective solution to model and apply planning domain knowledge for deliberation and action in probabilistic, agent-oriented control is presented. Specifically, the addition of a task structure planning component and supporting components to an agent-oriented architecture and agent implementation is described. For agent control in risky or uncertain environments, an approach and method of goal reduction to task plan sets and schedules of action is presented. Additionally, some issues related to component-wise, situation-dependent control of a task planning agent that schedules its tasks separately from planning them are motivated and discussed.

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