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Abstraction and approximate decision-theoretic planning
Artificial Intelligence 89 (1-2):219-283 (1997)
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Citations of this work
Practical solution techniques for first-order MDPs.Scott Sanner & Craig Boutilier - 2009 - Artificial Intelligence 173 (5-6):748-788.
Stochastic dynamic programming with factored representations.Craig Boutilier, Richard Dearden & Moisés Goldszmidt - 2000 - Artificial Intelligence 121 (1-2):49-107.
Equivalence notions and model minimization in Markov decision processes.Robert Givan, Thomas Dean & Matthew Greig - 2003 - Artificial Intelligence 147 (1-2):163-223.
Multiple perspective dynamic decision making.Tze Yun Leong - 1998 - Artificial Intelligence 105 (1-2):209-261.
Efficient incremental planning and learning with multi-valued decision diagrams.Jean-Christophe Magnan & Pierre-Henri Wuillemin - 2017 - Journal of Applied Logic 22:63-90.
References found in this work
Strips: A new approach to the application of theorem proving to problem solving.Richard E. Fikes & Nils J. Nilsson - 1971 - Artificial Intelligence 2 (3-4):189-208.
Planning in a hierarchy of abstraction spaces.Earl D. Sacerdoti - 1974 - Artificial Intelligence 5 (2):115-135.
Learning to act using real-time dynamic programming.Andrew G. Barto, Steven J. Bradtke & Satinder P. Singh - 1995 - Artificial Intelligence 72 (1-2):81-138.
Automatically generating abstractions for planning.Craig A. Knoblock - 1994 - Artificial Intelligence 68 (2):243-302.
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