Sciweavers

473 search results - page 28 / 95
» Optimal policy switching algorithms for reinforcement learni...
Sort
View
ICML
2009
IEEE
14 years 8 months ago
Monte-Carlo simulation balancing
In this paper we introduce the first algorithms for efficiently learning a simulation policy for Monte-Carlo search. Our main idea is to optimise the balance of a simulation polic...
David Silver, Gerald Tesauro
ATAL
2008
Springer
13 years 9 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
ICMLA
2010
13 years 5 months ago
Multimodal Parameter-exploring Policy Gradients
Abstract-- Policy Gradients with Parameter-based Exploration (PGPE) is a novel model-free reinforcement learning method that alleviates the problem of high-variance gradient estima...
Frank Sehnke, Alex Graves, Christian Osendorfer, J...
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 6 months ago
Generalized model learning for Reinforcement Learning on a humanoid robot
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
Todd Hester, Michael Quinlan, Peter Stone
ECAI
2008
Springer
13 years 9 months ago
Exploiting locality of interactions using a policy-gradient approach in multiagent learning
In this paper, we propose a policy gradient reinforcement learning algorithm to address transition-independent Dec-POMDPs. This approach aims at implicitly exploiting the locality...
Francisco S. Melo