85 search results - page 11 / 17 » Solving Stochastic Planning Problems with Large State and Ac... |
ICML
2001
IEEE
14 years 8 months ago
2001
IEEE
Direct policy search is a practical way to solve reinforcement learning problems involving continuous state and action spaces. The goal becomes finding policy parameters that maxi...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
IROS
2009
IEEE
14 years 2 months ago
2009
IEEE
Abstract— LDP (Locally Distributed Predicates) is a distributed, high-level language for programming modular reconfigurable robot systems (MRRs). In this paper we present the im...
AIPS
2000
13 years 8 months ago
2000
Planners from the family of Graphplan (Graphplan, IPP, STAN...) are presently considered as the most efficient ones on numerous planning domains. Their partially ordered plans can...
CDC
2010
IEEE
13 years 2 months ago
2010
IEEE
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...