Solving Time-critical Decision-making Problems with Predictable Computational Demands

In this work we present an approach to solving time-critical decision-making problems by taking advantage of domain structure to expand the amountof time available for processing difficult combinatorial tasks. Our approach uses predictable variability in computational demands to allocate on-line deliberation time and exploits problem regularity and stochastic models of environmental dynamics to restrict attention to small subsets of the state space. This approach demonstrates howslow, high-level systems(e.g., for planning and scheduling) might interact with faster, morereactive systems (e.g., for real-time execution and monitoring) and enables us to generate timely solutions to difficult combinatorial planning and scheduling problems such as air traffic control.

• Type: Conference
• Year: 1994
• Where: AIPS
• Authors: Thomas Dean, Lloyd Greenwald
• Keywords: AIPS 1994, Artificial Intelligence, Difficult Combinatorial Planning, Difficult Combinatorial Tasks, Time-critical Decision-making Problems