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» Knowledge States: A Tool for Randomized Online Algorithms
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ECML
2007
Springer
13 years 11 months ago
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass
ICWE
2004
Springer
14 years 22 days ago
Automatic Interpretation of Natural Language for a Multimedia E-learning Tool
Abstract. This paper describes the new e-learning tool CHESt that allows students to search in a knowledge base for short (teaching) multimedia clips by using a semantic search eng...
Serge Linckels, Christoph Meinel
JMLR
2010
130views more  JMLR 2010»
13 years 2 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...
DAGSTUHL
1996
13 years 8 months ago
Competitive Analysis of Distributed Algorithms
Abstract. Most applications of competitive analysis have involved online problems where a candidate on-line algorithm must compete on some input sequence against an optimal o -line...
James Aspnes
PUK
2000
13 years 8 months ago
Knowledge-Based Control of Decision Theoretic Planning - Adaptive Planning Model Selection
This paper proposes a new planning architecture for agents operating in uncertain and dynamic environments. Decisiontheoretic planning has been recognized as a useful tool for rea...
Jun Miura, Yoshiaki Shirai