43 search results - page 3 / 9 » The O.D.E. Method for Convergence of Stochastic Approximatio... |
NIPS
1993
13 years 10 months ago
1993
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
ICML
1998
IEEE
14 years 9 months ago
1998
IEEE
In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
AAMAS
2007
Springer
13 years 8 months ago
2007
Springer
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
JAIR
2002
13 years 8 months ago
2002
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
ICML
2000
IEEE
14 years 9 months ago
2000
IEEE
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...