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» Termination Analysis with Algorithmic Learning
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PRICAI
2000
Springer
15 years 6 months ago
Generating Hierarchical Structure in Reinforcement Learning from State Variables
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
Bernhard Hengst
101
Voted
ATAL
2009
Springer
15 years 9 months ago
SarsaLandmark: an algorithm for learning in POMDPs with landmarks
Reinforcement learning algorithms that use eligibility traces, such as Sarsa(λ), have been empirically shown to be effective in learning good estimated-state-based policies in pa...
Michael R. James, Satinder P. Singh
NEUROSCIENCE
2001
Springer
15 years 7 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar
112
Voted
IJCNN
2006
IEEE
15 years 8 months ago
Optimal In-Place Learning and the Lobe Component Analysis
— It is difficult to map many existing learning algorithms onto biological networks because the former require a separate learning network. The computational basis of biological...
Juyang Weng, Nan Zhang 0002
121
Voted
ECML
2004
Springer
15 years 8 months ago
An Analysis of Stopping and Filtering Criteria for Rule Learning
Abstract. In this paper, we investigate the properties of commonly used prepruning heuristics for rule learning by visualizing them in PN-space. PN-space is a variant of ROC-space,...
Johannes Fürnkranz, Peter A. Flach