Deliberation scheduling for problem solving in time-constrained environments

DOI10.1016/0004-3702(94)90054-XzbMath0809.68103OpenAlexW2020246567MaRDI QIDQ1329363

Thomas L. Dean, Mark Boddy

Publication date: 4 July 1994

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0004-3702(94)90054-x

zbMATH Keywords

decision-making proceduresdeliberation scheduling

Mathematics Subject Classification ID

Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (21)

Learning dynamic algorithm portfolios ⋮ Coalitions among computationally bounded agents ⋮ HEURISTIC SEARCH UNDER CONTRACT ⋮ Abstraction and approximate decision-theoretic planning. ⋮ Combining VNS with constraint programming for solving anytime optimization problems ⋮ Deliberation scheduling using GSMDPs in stochastic asynchronous domains ⋮ On-line resources allocation for ATM networks with rerouting ⋮ Optimal schedules for monitoring anytime algorithms ⋮ Iterative state-space reduction for flexible computation ⋮ Monitoring and control of anytime algorithms: A dynamic programming approach ⋮ Principles and applications of continual computation ⋮ Searching stochastically generated multi-abstraction-level design spaces ⋮ Bounding probabilistic relationships in Bayesian networks using qualitative influences: methods and applications ⋮ PROBLEM SOLVING WITH INSUFFICIENT RESOURCES ⋮ A model of anytime algorithm performance for bi-objective optimization ⋮ Constraint satisfaction for robust parsing of spoken language ⋮ Bargaining with limited computation: Deliberation equilibrium ⋮ Remote Agent: to boldly go where no AI system has gone before ⋮ Feature Subset Selection by Bayesian network-based optimization ⋮ Satisfying constraint sets through convex envelopes ⋮ Evaluation of Bayesian networks with flexible state-space abstraction methods

Cites Work

• Principles of metareasoning
• Optimal problem-solving search: All-or-none solutions
• Real-time heuristic search
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