Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
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...
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...
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...
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...