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ICML
2003
IEEE
16 years 7 months ago
AWESOME: A General Multiagent Learning Algorithm that Converges in Self-Play and Learns a Best Response Against Stationary Oppon
A satisfactory multiagent learning algorithm should, at a minimum, learn to play optimally against stationary opponents and converge to a Nash equilibrium in self-play. The algori...
Vincent Conitzer, Tuomas Sandholm
GECCO
2000
Springer
114views Optimization» more  GECCO 2000»
15 years 10 months ago
Intelligent Recombination Using Individual Learning in a Collective Learning Genetic Algorithm
This paper introduces a new collective learning genetic algorithm (CLGA) which employs individual learning to do intelligent recombination based on a cooperative exchange of knowl...
Terry P. Riopka, Peter Bock
ICANN
2003
Springer
15 years 11 months ago
Confidence Estimation Using the Incremental Learning Algorithm, Learn++
Pattern recognition problems span a broad range of applications, where each application has its own tolerance on classification error. The varying levels of risk associated with ma...
Jeffrey Byorick, Robi Polikar
AAAI
1996
15 years 7 months ago
A Complexity Analysis of Space-Bounded Learning Algorithms for the Constraint Satisfaction Problem
Learning during backtrack search is a space-intensive process that records information (such as additional constraints) in order to avoid redundant work. In this paper, we analyze...
Roberto J. Bayardo Jr., Daniel P. Miranker
STOC
1997
ACM
129views Algorithms» more  STOC 1997»
15 years 10 months ago
Better Bounds for Online Scheduling
We study a classical problem in online scheduling. A sequence of jobs must be scheduled on m identical parallel machines. As each job arrives, its processing time is known. The goa...
Susanne Albers