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» Parametric POMDPs for planning in continuous state spaces
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ECML
2007
Springer
15 years 1 months ago
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass
SIGMOD
2004
ACM
164views Database» more  SIGMOD 2004»
15 years 10 months ago
Dynamic Plan Migration for Continuous Queries Over Data Streams
Dynamic plan migration is concerned with the on-the-fly transition from one continuous query plan to a semantically equivalent yet more efficient plan. Migration is important for ...
Yali Zhu, Elke A. Rundensteiner, George T. Heinema...
AIPS
1996
14 years 11 months ago
Planning Experiments: Resolving Interactions between Two Planning Spaces
Learning from experimentation allows a system to acquire planning domain knowledge by correcting its knowledge when an action execution fails. Experiments are designed and planned...
Yolanda Gil
AIPS
2009
14 years 11 months ago
Computing Robust Plans in Continuous Domains
We define the robustness of a sequential plan as the probability that it will execute successfully despite uncertainty in the execution environment. We consider a rich notion of u...
Christian Fritz, Sheila A. McIlraith
RSS
2007
147views Robotics» more  RSS 2007»
14 years 11 months ago
Discrete Search Leading Continuous Exploration for Kinodynamic Motion Planning
Abstract— This paper presents the Discrete Search Leading continuous eXploration (DSLX) planner, a multi-resolution approach to motion planning that is suitable for challenging p...
Erion Plaku, Lydia E. Kavraki, Moshe Y. Vardi