Abstract. This paper illustrates how the Quadratic Assignment Problem (QAP) is used as a mathematical model that helps to produce a visualization of microarray data, based on the r...
Mario Inostroza-Ponta, Alexandre Mendes, Regina Be...
There has been some ambiguity about the growth of attractors in Kauffman networks with network size. Some recent work has linked this to the role and growth of circuits or loops o...
Previous research has shown that artificial immune systems can be used to produce robust schedules in a manufacturing environment. The main goal is to develop building blocks (anti...
Salwani Abdullah, Uwe Aickelin, Edmund K. Burke, A...
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
Abstract. In agent-based computational economics, many different trading strategies have been proposed. Given the kinds of market that such trading strategies are employed in, it i...
For a number of years we have been working towards the goal of automatically creating auction mechanisms, using a range of techniques from evolutionary and multi-agent learning. Th...
Steve Phelps, Kai Cai, Peter McBurney, Jinzhong Ni...
Abstract. The application of reinforcement learning algorithms to multiagent domains may cause complex non-convergent dynamics. The replicator dynamics, commonly used in evolutiona...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Fa...
Abstract. We study optimal control in large stochastic multi-agent systems in continuous space and time. We consider multi-agent systems where agents have independent dynamics with...