Co-evolution of Language and Behaviour in Autonomous Robots

This work explores the co-evolution and correlation between language use and be-havioural learning in a realistic simulated environment of robotic agents. Experiments involving different environmental setups, population sizes and learning schemes are used to study the conditions under which language can emerge and stabilise and how it affects the collective behaviour of the agents using it. The simulated agents are given a survival task of collecting balls and depositing them in bins in return for energy. The robots must learn to cooperate in order to achieve higher performance, which is an in-centive for developing and using language. The aim of the study is to explore whether learning language together with simple survival skills can lead not to an overhead in complexity, but work as a tool for a more rapid emergence of increasingly intelligent behaviour. Results stress the difficulty of language development and stabilisation, but also show how in an environment where cooperation is highly beneficial, language can sta-bilise over time to help coordinate the behaviours of individual agents and improve th