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A Closer Look at Adaptation Mechanisms in Simulated Environment-Driven Evolutionary Swarm Robotics

Steyven, Andreas Siegfried Wilhelm

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Abstract

This thesis investigates several aspects of environment-driven adaptation in simulated evolutionary swarm robotics. It is centred around a specific algorithm for distributed embodied evolution called mEDEA.
Firstly, mEDEA is extended with an explicit relative fitness measure while still maintaining the distributed nature of the algorithm. Two ways of using the relative fitness are investigated: influencing the spreading of genomes and performing an explicit genome selection. Both methods lead to an improvement in the swarm’s ability to maintain energy over longer periods.
Secondly, a communication energy model is derived and introduced into the simulator to investigate the influence of accounting for the costs of communication in the distributed evolutionary algorithm where communication is a key component.
Thirdly, a method is introduced that relates environmental conditions to a measure of the swarm’s behaviour in a 3-dimensional map to study the environment’s influence on the emergence of behaviours at the individual and swarm level. Interesting regions for further experimentation are identified in which algorithm specific characteristics show effect and can be explored.
Finally, a novel individual learning method is developed and used to investigate how the most effective balance between evolutionary and lifetime-adaptation mechanisms is influenced by aspects of the environment a swarm operates in. The results show a clear link between the effectiveness of different adaptation mechanisms and environmental conditions, specifically the rate of change and the availability of learning opportunities.

Citation

Steyven, A. S. W. A Closer Look at Adaptation Mechanisms in Simulated Environment-Driven Evolutionary Swarm Robotics. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/1253630

Thesis Type Thesis
Deposit Date Jul 20, 2018
Publicly Available Date Jul 20, 2018
Keywords Computer science, swarm robotics, artificial intelligence
Public URL http://researchrepository.napier.ac.uk/Output/1253630
Contract Date Jul 20, 2018
Award Date 2017-10

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Copyright in the text of this thesis rests with the author. Copies (by any process) either in full, or of extracts, may be made only in accordance with instructions given by the author and lodged in the Edinburgh Napier University library. Details may be obtained from the librarian. This page must form part of any such copies made.
Further copies (by any process) of copies made in accordance with such instructions may not be made without the written permission of the author. The ownership of any intellectual property rights which may be described in this thesis is vested in Edinburgh Napier University, subject to any prior agreement to the contrary, and may not be made available for use by third parties without the written permission of the university, which will prescribe the terms and conditions of any such agreement.






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