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PDDL+: Modelling Continuous Time-dependent Effects

by Maria Fox, Derek Long
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Extending PDDL to Model Stochastic Decision Processes

by HÃ¥kan L. S. Younes , 2003
"... We present an extension of PDDL for modeling stochastic decision processes. Our domain description language allows the specification of actions with probabilistic effects, exogenous events, and actions and events with delayed effects. The result is a language that can be used to specify stochast ..."
Abstract - Cited by 4 (0 self) - Add to MetaCart
We present an extension of PDDL for modeling stochastic decision processes. Our domain description language allows the specification of actions with probabilistic effects, exogenous events, and actions and events with delayed effects. The result is a language that can be used to specify stochastic decision processes, both discrete-time and continuous-time, of varying complexity. We also propose the use of established logic formalisms, taken from the model checking community, for specifying probabilistic temporally extended goals.

Journal of Artificial Intelligence Research 20 (2003) 149-154 Submitted 9/03; published 12/03 Commentary

by The Case For, David E. Smith - Journal of AI Research , 2003
"... The addition of durative actions to PDDL2.1 sparked some controversy. Fox and Long argued that actions should be considered as instantaneous, but can start and stop processes. ..."
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The addition of durative actions to PDDL2.1 sparked some controversy. Fox and Long argued that actions should be considered as instantaneous, but can start and stop processes.
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