The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
This paper presents a genetic programming-based symbolic regression approach to the construction of relational features in link analysis applications. Specifically, we consider t...
Tim Weninger, William H. Hsu, Jing Xia, Waleed Alj...
Abstract- We present experiments (co)evolving Go players based on artificial neural networks (ANNs) for a 5x5 board. ANN structure and weights are encoded in multi–chromosomal g...
— We introduce galsC, a language designed for programming event-driven embedded systems such as sensor networks. galsC implements the TinyGALS programming model. At the local lev...
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy but may behave differently due to position-dependent inputs. All...