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» Reinforcement Learning: An Introduction
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ATAL
2008
Springer
14 years 10 days ago
Approximate predictive state representations
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
Britton Wolfe, Michael R. James, Satinder P. Singh
NIPS
2001
13 years 11 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr
ML
2000
ACM
150views Machine Learning» more  ML 2000»
13 years 10 months ago
Adaptive Retrieval Agents: Internalizing Local Context and Scaling up to the Web
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
Filippo Menczer, Richard K. Belew
MICAI
2010
Springer
13 years 8 months ago
Teaching a Robot to Perform Tasks with Voice Commands
The full deployment of service robots in daily activities will require the robot to adapt to the needs of non-expert users, particularly, to learn how to perform new tasks from “...
Ana C. Tenorio-Gonzalez, Eduardo F. Morales, Luis ...
AIWORC
2000
IEEE
14 years 2 months ago
Distance Learning Using Web-Based Multimedia Environment
The "schooling industry" is faced with an inescapable demand to redefine its endeavors in terms of producing learning, rather than providing instructions. We propose a h...
Khalid J. Siddiqui, Junaid Ahmed Zubairi