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ECAI
2010
Springer
15 years 22 days ago
Learning action effects in partially observable domains
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
Kira Mourão, Ronald P. A. Petrick, Mark Ste...
JAIR
2008
107views more  JAIR 2008»
14 years 11 months ago
Planning with Durative Actions in Stochastic Domains
Probabilistic planning problems are typically modeled as a Markov Decision Process (MDP). MDPs, while an otherwise expressive model, allow only for sequential, non-durative action...
Mausam, Daniel S. Weld
AIPS
2004
15 years 1 months ago
Fault Tolerant Planning: Toward Probabilistic Uncertainty Models in Symbolic Non-Deterministic Planning
Symbolic non-deterministic planning represents action effects as sets of possible next states. In this paper, we move toward a more probabilistic uncertainty model by distinguishi...
Rune M. Jensen, Manuela M. Veloso, Randal E. Bryan...
AIPS
1994
15 years 29 days ago
Probabilistic Planning with Information Gathering and Contingent Execution
MostAI representations and algorithms for plan generation havenot included the concept of informationproducingactions (also called diagnostics, or tests, in the decision making li...
Denise Draper, Steve Hanks, Daniel S. Weld
AIPS
2008
15 years 2 months ago
Useless Actions Are Useful
Planning as heuristic search is a powerful approach to solving domain independent planning problems. In recent years, various successful heuristics and planners like FF, LPG, FAST...
Martin Wehrle, Sebastian Kupferschmid, Andreas Pod...