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GECCO
2005
Springer
139views Optimization» more  GECCO 2005»
14 years 4 months ago
Event-driven learning classifier systems for online soccer games
This paper reports on the application of classifier systems to the acquisition of decision-making algorithms for agents in online soccer games. The objective of this research is t...
Yuji Sato, Ryutaro Kanno
GECCO
2009
Springer
14 years 3 months ago
Novelty of behaviour as a basis for the neuro-evolution of operant reward learning
An agent that deviates from a usual or previous course of action can be said to display novel or varying behaviour. Novelty of behaviour can be seen as the result of real or appar...
Andrea Soltoggio, Ben Jones
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
14 years 2 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
ATAL
2006
Springer
14 years 2 months ago
Learning the required number of agents for complex tasks
Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are un...
Sébastien Paquet, Brahim Chaib-draa
ATAL
2006
Springer
14 years 2 months ago
Learning to identify winning coalitions in the PAC model
We consider PAC learning of simple cooperative games, in which the coalitions are partitioned into "winning" and "losing" coalitions. We analyze the complexity...
Ariel D. Procaccia, Jeffrey S. Rosenschein