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AAMAS
2002
Springer
15 years 6 months ago
Cooperative Multiagent Learning
Cooperation and learning are two ways in which an agent can improve its performance. Cooperative Multiagent Learning is a framework to analyze the tradeoff between cooperation and ...
Enric Plaza, Santiago Ontañón
FSS
2010
147views more  FSS 2010»
15 years 4 months ago
A divide and conquer method for learning large Fuzzy Cognitive Maps
Fuzzy Cognitive Maps (FCMs) are a convenient tool for modeling and simulating dynamic systems. FCMs were applied in a large number of diverse areas and have already gained momentu...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz
ICML
1995
IEEE
16 years 7 months ago
Residual Algorithms: Reinforcement Learning with Function Approximation
A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that ...
Leemon C. Baird III
KDD
2007
ACM
149views Data Mining» more  KDD 2007»
16 years 6 months ago
Partial example acquisition in cost-sensitive learning
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
Victor S. Sheng, Charles X. Ling
ALT
2008
Springer
16 years 3 months ago
Learning with Temporary Memory
In the inductive inference framework of learning in the limit, a variation of the bounded example memory (Bem) language learning model is considered. Intuitively, the new model con...
Steffen Lange, Samuel E. Moelius, Sandra Zilles