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» Model-Based Exploration in Continuous State Spaces
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COLT
2008
Springer
13 years 7 months ago
Adaptive Aggregation for Reinforcement Learning with Efficient Exploration: Deterministic Domains
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
Andrey Bernstein, Nahum Shimkin
ECML
2007
Springer
13 years 9 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
FGR
2011
IEEE
244views Biometrics» more  FGR 2011»
12 years 9 months ago
Emotion representation, analysis and synthesis in continuous space: A survey
— Despite major advances within the affective computing research field, modelling, analysing, interpreting and responding to naturalistic human affective behaviour still remains...
Hatice Gunes, Björn Schuller, Maja Pantic, Ro...
RSS
2007
147views Robotics» more  RSS 2007»
13 years 7 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
IROS
2008
IEEE
151views Robotics» more  IROS 2008»
13 years 12 months ago
Transition-based RRT for path planning in continuous cost spaces
This paper presents a new method called Transition-based RRT (T-RRT) for path planning problems in continuous cost spaces. It combines the exploration strength of the RRT algorith...
Leonard Jaillet, Juan Cortés, Thierry Sim&e...