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GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
15 years 3 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 3 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
GECCO
2010
Springer
187views Optimization» more  GECCO 2010»
15 years 3 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
ATAL
2008
Springer
15 years 1 months ago
A domain specific modeling language for multiagent systems
Software systems are becoming more and more complex with a large number of interacting partners often distributed over a network. A common dilemma faced by software engineers in b...
Christian Hahn
ATAL
2008
Springer
15 years 1 months ago
Cooperative search for optimizing pipeline operations
We present an application of a multi-agent cooperative search approach to the problem of optimizing gas pipeline operations, i.e. finding control parameters for a gas transmission...
T. Mora, Abu B. Sesay, Jörg Denzinger, Hossei...