Neuroevolution is a promising learning method in tasks with extremely large state and action spaces and hidden states. Recent advances allow neuroevolution to take place in real t...
Chern Han Yong, Kenneth O. Stanley, Risto Miikkula...
A common challenge for agents in multiagent systems is trying to predict what other agents are going to do in the future. Such knowledge can help an agent determine which of its c...
In learning belief networks, the single link lookahead search is widely adopted to reduce the search space. We show that there exists a class of probabilistic domain models which ...
Several variants of the Particle Swarm Optimization (PSO) algorithm have been proposed in recent past to tackle the multi-objective optimization problems based on the concept of Pa...
Recently, many researchers have designed neural network architectures with evolutionary algorithms but most of them have used only the fittest solution of the last generation. To ...