A genetic programming method is investigated for optimizing both the architecture and the connection weights of multilayer feedforward neural networks. The genotype of each networ...
We investigated how indexed FOR-loops, such as the ones found in procedural programming languages, can be implemented in genetic programming. We use them to train programs that le...
We investigate a bi-variate probabilistic model-building GA for the graph bipartitioning problem. The graph bipartitioning problem is a grouping problem that requires some modifi...
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
Abstract— This paper investigates optimal routing and adaptive scheduling in a wireless mesh network composed of mesh clients and mesh routers. The mesh clients are power constra...