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GECCO
2010
Springer
187views Optimization» more  GECCO 2010»
13 years 11 months ago
Evolving agent behavior in multiobjective domains using fitness-based shaping
Multiobjective evolutionary algorithms have long been applied to engineering problems. Lately they have also been used to evolve behaviors for intelligent agents. In such applicat...
Jacob Schrum, Risto Miikkulainen
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolving computer intrusion scripts for vulnerability assessment and log analysis
Evolutionary computation is used to construct undetectable computer attack scripts. Using a simulated operating system, we show that scripts can be evolved to cover their tracks a...
Julien Budynek, Eric Bonabeau, Ben Shargel
ICML
1999
IEEE
14 years 8 months ago
Distributed Value Functions
Many interesting problems, such as power grids, network switches, and tra c ow, that are candidates for solving with reinforcement learningRL, alsohave properties that make distri...
Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore...
NIPS
2001
13 years 9 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr
GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
14 years 1 months ago
A destructive evolutionary process: a pilot implementation
This paper describes the application of evolutionary search to the problem of Flash memory wear-out. The operating parameters of Flash memory are notoriously difficult to determin...
Joe Sullivan, Conor Ryan