Reasoning in Real-Time for the Pilot Associate: An Examination of a Model Based Approach to Reasoning in Real-Time for Artificial Intelligence Systems Using a Distributed Architecture.
Abstract
The use of artificial intelligence (AI) techniques for pilot aiding in real-time (DoD Pilot Associate--PA) introduces some seemingly intractable problems. Most algorithms which will be used in a PA are search intensive with exponential-order-time-co mplexities. The thesis outlines the problem and explores the possibility of using parallel processing for minimizing the computational costs. Methods for, and results from, distributing data and functions among many processors are presented. An extension to the blackboard structure used in many AI systems called a 'virtual blackboard' is introduced. The results and techniques are bundled into a prototype distributed data-flow constraint-network application system called DDAFCON. DDAFCON is discussed, and a flight-planning application is presented using DDAFCON. The results are discussed. It is shown that the maximum speedup due to parallel processing is bounded by the number of processors which a problem solution can accept. The thesis concludes that generalized AI structures and reasoning paradigms (specifically, 'deep models'), although seemingly required for the performance level desired for applications such as the PA may not be realizable for many real-time applications. A change in emphasis for developing real-time AI systems is suggested.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1985
- Accession Number
- ADA163947
Entities
People
- Douglas O. Norman
Organizations
- Air Force Institute of Technology