Modeling a dynamic and uncertain world. I: Symbolic and probabilistic reasoning about change

DOI10.1016/0004-3702(94)90002-7zbMath0803.68121OpenAlexW1552176201MaRDI QIDQ1321053

Drew McDermott, Steve Hanks

Publication date: 3 May 1994

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

Full work available at URL: https://doi.org/10.1016/0004-3702(94)90002-7

zbMATH Keywords

planningsymbolic reasoningprobabilistic temporal reasoning

Mathematics Subject Classification ID

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

Related Items (8)

Efficient incremental planning and learning with multi-valued decision diagrams ⋮ Interpreting a dynamic and uncertain world: task-based control ⋮ A logic of time, chance, and action for representing plans ⋮ Dynamic reasoning with qualified syllogisms ⋮ Changing times: a causal theory of probabilistic temporal reasoning ⋮ Stochastic dynamic programming with factored representations ⋮ Contingent planning under uncertainty via stochastic satisfiability ⋮ Equivalence notions and model minimization in Markov decision processes

Cites Work

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• Causality and maximum entropy updating
• Diagnosing multiple faults
• Nonmonotonic logic and temporal projection
• Papers on probability, statistics and statistical physics. Ed. by R. D. Rosenkrantz.
• Reasoning about partially ordered events
• Dynamic programming and influence diagrams

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