RIA: Optimal Resource-Bounded Reasoning Using Compilation and Monitoring of Anytime Algorithms

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9409827 Zilberstein This project is aimed at developing a decision-theoretic, adaptive approach to building systems that can perform robustly a variety of real-time tasks. Such tasks include medical diagnosis job scheduling, and robot navigation. In almost all cases, the deliberation required to select optimal actions degrades the system's overall utility. It is by now well-understood that a successful system must trade off decision quality for deliberation cost. Over the past several years, work by Dean, Horvitz, Russell, Zilberstein, and others has shown that anytime algorithms are a useful tool for real-time system design, since they allow computation time to be larger systems from smaller, reusable anytime modules. The proposed solution to this problem is based on novel off-line compilation process and run-time monitoring that can maximize the overall utility of the system. This research will produce a new architecture for resource-bounded reasoning. The study will cover the problem of constructing anytime algorithms, the representation and manipulation of conditional performance profiles, and the development of efficient compilation and monitoring procedures for systems composed of anytime algorithms.