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» Compositional Models for Reinforcement Learning
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ISCAS
2002
IEEE
153views Hardware» more  ISCAS 2002»
14 years 21 days ago
Biological learning modeled in an adaptive floating-gate system
We have implemented an aspect of learning and memory in the nervous system using analog electronics. Using a simple synaptic circuit we realize networks with Hebbian type adaptati...
Christal Gordon, Paul E. Hasler
ICML
1998
IEEE
14 years 8 months ago
Intra-Option Learning about Temporally Abstract Actions
tion Learning about Temporally Abstract Actions Richard S. Sutton Department of Computer Science University of Massachusetts Amherst, MA 01003-4610 rich@cs.umass.edu Doina Precup D...
Richard S. Sutton, Doina Precup, Satinder P. Singh
LWA
2007
13 years 9 months ago
Towards Learning User-Adaptive State Models in a Conversational Recommender System
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
Tariq Mahmood, Francesco Ricci
AAAI
2000
13 years 9 months ago
ADVISOR: A Machine Learning Architecture for Intelligent Tutor Construction
We have constructed ADVISOR, a two-agent machine learning architecture for intelligent tutoring systems (ITS). The purpose of this architecture is to centralize the reasoning of a...
Joseph Beck, Beverly Park Woolf, Carole R. Beal
IWCLS
2007
Springer
14 years 1 months ago
On Lookahead and Latent Learning in Simple LCS
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Larry Bull