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» Learning Polyhedral Classifiers Using Logistic Function
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ECML
2004
Springer
14 years 1 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner
SAC
2005
ACM
14 years 1 months ago
Learning decision trees from dynamic data streams
: This paper presents a system for induction of forest of functional trees from data streams able to detect concept drift. The Ultra Fast Forest of Trees (UFFT) is an incremental a...
João Gama, Pedro Medas, Pedro Pereira Rodri...
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
13 years 11 months ago
Standard and averaging reinforcement learning in XCS
This paper investigates reinforcement learning (RL) in XCS. First, it formally shows that XCS implements a method of generalized RL based on linear approximators, in which the usu...
Pier Luca Lanzi, Daniele Loiacono
FLAIRS
2010
13 years 10 months ago
Learning to Identify and Track Imaginary Objects Implied by Gestures
A vision-based machine learner is presented that learns characteristic hand and object movement patterns for using certain objects, and uses this information to recreate the "...
Andreya Piplica, Alexandra Olivier, Allison Petros...
EC
2006
121views ECommerce» more  EC 2006»
13 years 7 months ago
A Study of Structural and Parametric Learning in XCS
The performance of a learning classifier system is due to its two main components. First, it evolves new structures by generating new rules in a genetic process; second, it adjust...
Tim Kovacs, Manfred Kerber