Date of Award

12-1992

Document Type

Thesis

Degree Name

Master of Science in Computer Engineering

Department

Department of Electrical and Computer Engineering

First Advisor

Gregg H. Gunsch, PhD

Abstract

Conventional real-time systems are fully deterministic allowing for off-line, optimal, task scheduling under all circumstances. Real-time intelligent systems add non-deterministic task execution times and non- deterministic task sets for scheduling purposes. Non-deterministic task sets force intelligent real-time systems to trade-off execution time with solution quality during run-time and perform dynamic task scheduling. Four basic design considerations addressing those tradeoffs have been identified: control reasoning, focus of attention, parallelism, and algorithm efficacy. Non-real- time intelligent systems contain an environment sensor, a model of the environment, a reasoning process, and a large collection of procedural processes. Real-time intelligent systems add to these a model of the real-time system's behavior, and a real-time task scheduler. In addition, the reasoning process is augmented with a metaplanner to reason about timing issues using the system's behavioral model. Additionally, real-time deadlines force the inclusion of pluralistic solution methods in the intelligent system to allow multiple responses ranging from reactive to fully reasoned and calculated. This research presents an architecture capable of meeting real-time performance goals with on- line scheduling of tasks.

AFIT Designator

AFIT-GCE-ENG-92D-12

DTIC Accession Number

ADA259002

Comments

The author's Vita page is omitted.

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