Previous work has addressed the development of a framework to categorise and understand agent-based systems. It described and formalised an agent-hierarchy that included objects, ...
We propose an algorithm for efficient threshold network synthesis of arbitrary multi-output Boolean functions. The main purpose of this work is to bridge the wide gap that currentl...
This paper proposes a new algorithm which promotes well distributed non-dominated fronts in the parameters space when a single-objective function is optimized. This algorithm is b...
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
A weakness of classical Markov decision processes (MDPs) is that they scale very poorly due to the flat state-space representation. Factored MDPs address this representational pro...