Constrained by Design: Influence of Genetic Encodings on Evolved Traits of Robots

Author:

Miras Karine

Abstract

Genetic encodings and their particular properties are known to have a strong influence on the success of evolutionary systems. However, the literature has widely focused on studying the effects that encodings have on performance, i.e., fitness-oriented studies. Notably, this anchoring of the literature to performance is limiting, considering that performance provides bounded information about the behavior of a robot system. In this paper, we investigate how genetic encodings constrain the space of robot phenotypes and robot behavior. In summary, we demonstrate how two generative encodings of different nature lead to very different robots and discuss these differences. Our principal contributions are creating awareness about robot encoding biases, demonstrating how such biases affect evolved morphological, control, and behavioral traits, and finally scrutinizing the trade-offs among different biases.

Publisher

Frontiers Media SA

Subject

Artificial Intelligence,Computer Science Applications

Reference48 articles.

1. Environmental Influence on the Evolution of Morphological Complexity in Machines;Auerbach;Plos Comput. Biol.,2014

2. Robogen: Robot Generation through Artificial Evolution;Auerbach,2014

3. Modularity in Development and Why it Matters to Evo-Devo;Bolker;Am. Zool,2000

4. Evolving Modular Genetic Regulatory Networks;Bongard,2002

5. Bootstrapping Artificial Evolution to Design Robots for Autonomous Fabrication;Buchanan Berumen;MDPI Robotics,2020

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