We consider multi-agent systems whose agents compete for resources by striving to be in the minority group. The agents adapt to the environment by reinforcement learning of the pr...
Large systems of agents deployed in a real-world environment face threats to their problem solving performance that are independent of the complexity of the problem or the charact...
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Components in a decentralised system are faced with uncertainty as how to best adapt to a changing environment to maintain or optimise system performance. How can individual compo...
Traditional Web-based educational systems still have several shortcomings when comparing with a real-life classroom teaching, such as lack of contextual and adaptive support, lack...