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GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
13 years 11 months ago
Multi-agent task allocation: learning when to say no
This paper presents a communication-less multi-agent task allocation procedure that allows agents to use past experience to make non-greedy decisions about task assignments. Exper...
Adam Campbell, Annie S. Wu, Randall Shumaker
GECCO
2008
Springer
115views Optimization» more  GECCO 2008»
13 years 11 months ago
A genetic programming approach to business process mining
The aim of process mining is to identify and extract process patterns from data logs to reconstruct an overall process flowchart. As business processes become more and more comple...
Chris J. Turner, Ashutosh Tiwari, Jörn Mehnen
GECCO
2008
Springer
122views Optimization» more  GECCO 2008»
13 years 11 months ago
Varying portfolio construction of stocks using genetic network programming with control nodes
A new evolutionary method named “Genetic Network Programming with Control Nodes, GNPcn” has been proposed and applied to determine the timing of buying and selling stocks. GNP...
Etsushi Ohkawa, Yan Chen, Shingo Mabu, Kaoru Shima...
GECCO
2008
Springer
160views Optimization» more  GECCO 2008»
13 years 11 months ago
Self-managing agents for dynamic scheduling in manufacturing
The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using coo...
Ana Madureira, Filipe Santos, Ivo Pereira
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
13 years 11 months ago
Adapted Pittsburgh classifier system: building accurate strategies in non markovian environments
This paper focuses on the study of the behavior of a genetic algorithm based classifier system, the Adapted Pittsburgh Classifier System (A.P.C.S), on maze type environments con...
Gilles Énée, Mathias Péroumal...