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How do different encodings influence the performance of the MAP-Elites algorithm?

How do different encodings influence the performance of the MAP-Elites algorithm?
How do different encodings influence the performance of the MAP-Elites algorithm?
The recently introduced Intelligent Trial and Error algorithm (IT&E) both improves the ability to automatically generate controllers that transfer to real robots, and enables robots to creatively adapt to damage in less than 2 minutes. A key component of IT&E is a new evolutionary algorithm called MAP-Elites, which creates a behavior-performance map that is provided as a set of "creative" ideas to an online learning algorithm. To date, all experiments with MAP-Elites have been performed with a directly encoded list of parameters: it is therefore unknown how MAP-Elites would behave with more advanced encodings, like HyperNeat and SUPG. In addition, because we ultimately want robots that respond to their environments via sensors, we investigate the ability of MAP-Elites to evolve closed-loop controllers, which are more complicated, but also more powerful. Our results show that the encoding critically impacts the quality of the results of MAP-Elites, and that the differences are likely linked to the locality of the encoding (the likelihood of generating a similar behavior after a single mutation). Overall, these results improve our understanding of both the dynamics of the MAP-Elites algorithm and how to best harness MAP-Elites to evolve effective and adaptable robotic controllers.
173-180
ACM
Tarapore, Danesh
fe8ec8ae-1fad-4726-abef-84b538542ee4
Clune, Jeff
2a9284aa-86d9-4279-aefe-c938cf31ad4d
Cully, Antoine
ae321e02-82f4-44cb-bfa0-31a265ebaaf1
Mouret, Jean-Baptiste
a837dbc0-1852-4e6f-93d8-41d927305eaf
Tarapore, Danesh
fe8ec8ae-1fad-4726-abef-84b538542ee4
Clune, Jeff
2a9284aa-86d9-4279-aefe-c938cf31ad4d
Cully, Antoine
ae321e02-82f4-44cb-bfa0-31a265ebaaf1
Mouret, Jean-Baptiste
a837dbc0-1852-4e6f-93d8-41d927305eaf

Tarapore, Danesh, Clune, Jeff, Cully, Antoine and Mouret, Jean-Baptiste (2016) How do different encodings influence the performance of the MAP-Elites algorithm? In GECCO '16 Proceedings of the 2016 on Genetic and Evolutionary Computation Conference. ACM. pp. 173-180 . (doi:10.1145/2908812.2908875).

Record type: Conference or Workshop Item (Paper)

Abstract

The recently introduced Intelligent Trial and Error algorithm (IT&E) both improves the ability to automatically generate controllers that transfer to real robots, and enables robots to creatively adapt to damage in less than 2 minutes. A key component of IT&E is a new evolutionary algorithm called MAP-Elites, which creates a behavior-performance map that is provided as a set of "creative" ideas to an online learning algorithm. To date, all experiments with MAP-Elites have been performed with a directly encoded list of parameters: it is therefore unknown how MAP-Elites would behave with more advanced encodings, like HyperNeat and SUPG. In addition, because we ultimately want robots that respond to their environments via sensors, we investigate the ability of MAP-Elites to evolve closed-loop controllers, which are more complicated, but also more powerful. Our results show that the encoding critically impacts the quality of the results of MAP-Elites, and that the differences are likely linked to the locality of the encoding (the likelihood of generating a similar behavior after a single mutation). Overall, these results improve our understanding of both the dynamics of the MAP-Elites algorithm and how to best harness MAP-Elites to evolve effective and adaptable robotic controllers.

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More information

Published date: 2016
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 410786
URI: https://eprints.soton.ac.uk/id/eprint/410786
PURE UUID: 17d23fe6-b07b-454c-8d2e-cca10573bf5a
ORCID for Danesh Tarapore: ORCID iD orcid.org/0000-0002-3226-6861

Catalogue record

Date deposited: 09 Jun 2017 09:38
Last modified: 12 Nov 2019 01:28

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