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» Learning Rules for Adaptive Planning
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ATAL
2010
Springer
13 years 10 months ago
Planning against fictitious players in repeated normal form games
Planning how to interact against bounded memory and unbounded memory learning opponents needs different treatment. Thus far, however, work in this area has shown how to design pla...
Enrique Munoz de Cote, Nicholas R. Jennings
UM
2009
Springer
14 years 3 months ago
Evaluating Web Based Instructional Models Using Association Rule Mining
Abstract. In this paper we describe an Integrated Development System for Instructional Model for E-learning (INDESIME) to create and to maintain instructional models using adaptive...
Enrique García, Cristóbal Romero, Se...
ICML
2008
IEEE
14 years 9 months ago
Empirical Bernstein stopping
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
Csaba Szepesvári, Jean-Yves Audibert, Volod...
CIIA
2009
13 years 10 months ago
Dynamic Scheduling in Petroleum Process using Reinforcement Learning
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...
Nassima Aissani, Bouziane Beldjilali
AH
2000
Springer
14 years 1 months ago
A Connectionist Approach for Supporting Personalized Learning in a Web-Based Learning Environment
The paper investigates the use of computational intelligence for adaptive lesson presentation in a Web-based learning environment. A specialized connectionist architecture is devel...
Kyparisia A. Papanikolaou, George D. Magoulas, Mar...