560 search results - page 5 / 112 » From Continuous to Discrete Games |
AIIDE
2006
13 years 9 months ago
2006
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
APN
2005
Springer
14 years 1 months ago
2005
Springer
State explosion is a fundamental problem in the analysis and synthesis of discrete event systems. Continuous Petri nets can be seen as a relaxation of discrete models allowing more...
ATAL
2008
Springer
13 years 9 months ago
2008
Springer
We present Tartanian, a game theory-based player for headsup no-limit Texas Hold'em poker. Tartanian is built from three components. First, to deal with the virtually infinit...
CDC
2009
IEEE
14 years 11 days ago
2009
IEEE
— Multi-agent coordination problems can be cast as distributed optimization tasks. Probability Collectives (PCs) are techniques that deal with such problems in discrete and conti...
AAAI
2011
12 years 7 months ago
2011
Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...