We revisit memory hierarchy design viewing memory as an inter-operation communication agent. This perspective leads to the development of novel methods of performing inter-operati...
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
This paper examines the feasibility of using statistical methods to train a part-of-speech predictor for unknown words. By using statistical methods, without incorporating hand-cr...
Abstract-- A key indicator of problem difficulty in evolutionary computation problems is the landscape's locality, that is whether the genotype-phenotype mapping preserves nei...
Biologically focused, agent-based models need many parameters in order to simulate system dynamics. It is often essential to explore the consequences of many parameter vectors bef...