This paper investigates incremental multiagent learning in static or evolving structured networks. Learning examples are incrementally distributed among the agents, and the object...
Gauvain Bourgne, Amal El Fallah-Seghrouchni, Henry...
In standard neuro-evolution, a population of networks is evolved in a task, and the network that best solves the task is found. This network is then fixed and used to solve future...
Adrian K. Agogino, Kenneth O. Stanley, Risto Miikk...
In this paper, we study multi-agent economic systems using a recent approach to economic modeling called Agent-based Computational Economics (ACE): the application of the Complex ...
Abstract. Artificial agents controlled by dynamic recurrent node networks with fixed weights are evolved to search for food and associate it with one of two different temperatur...
Abstract. In [8] Yamauchi and Beer explored the abilities of continuous time recurrent neural networks (CTRNNs) to display reinforcementlearning like abilities. The investigated ta...