The use of latent semantic indexing to identify evolutionary trajectories in behaviour space

Abstract

This paper describes the simulation of a foraging agent in an environment with a simple ecological structure, alternatively using one of three different control systems with varying degrees of memory. These controllers are evolved to produce a range of emergent behaviours, which are analysed and compared using Latent Semantic Indexing (LSI): the behaviours are compared between controllers and in their evolutionary trajectories. It is argued that the ability of LSI to reduce large dimensional spaces to a lower dimensional representation which is easier to understand can help in highlighting key relationships in the complexity of interactions between agent and environment.