Building Resource-Bounded Reasoning Systems
Papers from the AAAI Workshop
Shlomo Zilberstein and Louis Hoebel, Cochairs
Technical Report WS-97-06
105 pp., $30.00
ISBN 978-1-57735-033-0
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Limited computational resources are a primary concern in almost every AI application. Since the mid-1980s, there has been a growing interest in the development of computational methods that offer a tradeoff between resource consumption and quality of results. Examples of active research areas in this emerging field include anytime algorithms, flexible computation techniques, imprecise computation, memory bounded search, and design-to-time scheduling. Researchers have developed a large body of knowledge that covers the construction, composition, and meta-level control of resource-bounded reasoning systems. The purpose of this workshop was to foster collaboration among researchers who share an interest in applications of resource-bounded reasoning in such areas as heuristic search, constraint satisfaction, probabilistic inference, planning and scheduling, signal interpretation, medical diagnosis and treatment, vision, graphics, and intelligent information gathering. What is common to all these problems is that it is not feasible (computationally) or desirable (economically) to compute the optimal answer. With a primary focus on applications, the workshop covered:
- Types of computational tradeoffs in reasoning and search
- Representation and measurement of computational tradeoffs
- Capturing the dependency of per-formance on problem instance "hardness"
- Embedding flexible computation components in large systems
- Run-time assessment and prediction of solution quality
- Run-time allocation of computa-tional resources
- Characterizing the overall perfor-mance of resource-bounded reason-ing systems