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ICRA
2009
IEEE
259views Robotics» more  ICRA 2009»
13 years 12 months ago
Constructing action set from basis functions for reinforcement learning of robot control
Abstract— Continuous action sets are used in many reinforcement learning (RL) applications in robot control since the control input is continuous. However, discrete action sets a...
Akihiko Yamaguchi, Jun Takamatsu, Tsukasa Ogasawar...
UAI
2004
13 years 6 months ago
Solving Factored MDPs with Continuous and Discrete Variables
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
JACM
2007
160views more  JACM 2007»
13 years 5 months ago
Lossless abstraction of imperfect information games
abstraction of imperfect information games ANDREW GILPIN and TUOMAS SANDHOLM Computer Science Department Carnegie Mellon University Pittsburgh, PA, USA Finding an equilibrium of an...
Andrew Gilpin, Tuomas Sandholm
SIGECOM
2006
ACM
135views ECommerce» more  SIGECOM 2006»
13 years 11 months ago
Finding equilibria in large sequential games of imperfect information
Finding an equilibrium of an extensive form game of imperfect information is a fundamental problem in computational game theory, but current techniques do not scale to large games...
Andrew Gilpin, Tuomas Sandholm
JMLR
2006
116views more  JMLR 2006»
13 years 5 months ago
Point-Based Value Iteration for Continuous POMDPs
We propose a novel approach to optimize Partially Observable Markov Decisions Processes (POMDPs) defined on continuous spaces. To date, most algorithms for model-based POMDPs are ...
Josep M. Porta, Nikos A. Vlassis, Matthijs T. J. S...