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» Evolution and learning in multiagent systems
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GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 9 months ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay
ARGMAS
2006
Springer
14 years 22 days ago
Arguments and Counterexamples in Case-Based Joint Deliberation
Multiagent learning can be seen as applying ML techniques to the core issues of multiagent systems, like communication, coordination, and competition. In this paper, we address the...
Santiago Ontañón, Enric Plaza
GECCO
2003
Springer
128views Optimization» more  GECCO 2003»
14 years 2 months ago
Learning Biped Locomotion from First Principles on a Simulated Humanoid Robot Using Linear Genetic Programming
We describe the first instance of an approach for control programming of humanoid robots, based on evolution as the main adaptation mechanism. In an attempt to overcome some of th...
Krister Wolff, Peter Nordin
EGICE
2006
14 years 20 days ago
Bio-inspiration: Learning Creative Design Principia
Reusing or modifying known design concepts cannot meet new challenges for engineering systems. However, engineers can find inspiration outside their traditional domains in order to...
Tomasz Arciszewski, Joanna Cornell
GECCO
2008
Springer
160views Optimization» more  GECCO 2008»
13 years 10 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