We present a novel approach to concept learning in which a coevolutionary genetic algorithm is applied to the construction of an immune system whose antibodies can discriminate bet...
Abstract. Symbolic state-space generators are notoriously hard to parallelise. However, the Saturation algorithm implemented in the SMART verification tool differs from other seque...
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
Multi-Terminal Binary Decision Diagrams (MTBDDs) have been successfully applied in symbolic model checking of probabilistic systems. In this paper we propose an encoding method for...
Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...