121 search results - page 7 / 25 » Toward Off-Policy Learning Control with Function Approximati... |
ML
2002
ACM
13 years 8 months ago
2002
ACM
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...
ECML
2006
Springer
14 years 22 days ago
2006
Springer
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
COLT
1992
Springer
14 years 1 months ago
1992
Springer
In this paper we initiatean investigationof generalizationsof the ProbablyApproximatelyCorrect (PAC) learningmodelthat attemptto significantlyweakenthe target functionassumptions.T...
ISCAS
2006
IEEE
14 years 3 months ago
2006
IEEE
— This paper describes a general approach for the unsupervised learning of behaviors in a behavior-based robot. The key idea is to formalize a behavior produced by a Motor Map dr...
ATAL
2008
Springer
13 years 11 months ago
2008
Springer
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...