FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3178268080> ?p ?o ?g. }

• W3178268080 endingPage "107688" @default.
• W3178268080 startingPage "107688" @default.
• W3178268080 abstract "The vision behind this paper looks ahead to evolutionary robot systems where morphologies and controllers are evolved together and ‘newborn’ robots undergo a learning process to optimize their inherited brain for the inherited body. The specific problem we address is learning controllers for the task of directed locomotion in evolvable modular robots. To this end, we present a test suite of robots with different shapes and sizes and compare two learning algorithms, Bayesian optimization and HyperNEAT. The experiments in simulation show that both methods obtain good controllers, but Bayesian optimization is more effective and sample efficient. We validate the best learned controllers by constructing three robots from the test suite in the real world and observe their fitness and actual trajectories. The obtained results indicate a reality gap, but overall the trajectories are adequate and follow the target directions successfully." @default.
• W3178268080 created "2021-07-19" @default.
• W3178268080 creator A5004385039 @default.
• W3178268080 creator A5005078316 @default.
• W3178268080 creator A5074492402 @default.
• W3178268080 creator A5081436755 @default.
• W3178268080 creator A5083106608 @default.
• W3178268080 creator A5091376805 @default.
• W3178268080 date "2021-11-01" @default.
• W3178268080 modified "2023-10-14" @default.
• W3178268080 title "Learning directed locomotion in modular robots with evolvable morphologies" @default.
• W3178268080 cites W1609223620 @default.
• W3178268080 cites W1738827650 @default.
• W3178268080 cites W1787284831 @default.
• W3178268080 cites W1987124340 @default.
• W3178268080 cites W2001685400 @default.
• W3178268080 cites W2017402562 @default.
• W3178268080 cites W2025888225 @default.
• W3178268080 cites W2048963734 @default.
• W3178268080 cites W2068025371 @default.
• W3178268080 cites W2083141675 @default.
• W3178268080 cites W2091742402 @default.
• W3178268080 cites W2097235959 @default.
• W3178268080 cites W2112413846 @default.
• W3178268080 cites W2119814172 @default.
• W3178268080 cites W2156174987 @default.
• W3178268080 cites W2165379011 @default.
• W3178268080 cites W2250150559 @default.
• W3178268080 cites W2341057945 @default.
• W3178268080 cites W2535437139 @default.
• W3178268080 cites W2584447397 @default.
• W3178268080 cites W2611179787 @default.
• W3178268080 cites W2615620594 @default.
• W3178268080 cites W2620944927 @default.
• W3178268080 cites W264800540 @default.
• W3178268080 cites W2701942770 @default.
• W3178268080 cites W2749701166 @default.
• W3178268080 cites W2793732783 @default.
• W3178268080 cites W2884997579 @default.
• W3178268080 cites W2914721205 @default.
• W3178268080 cites W2999228461 @default.
• W3178268080 cites W3105540415 @default.
• W3178268080 cites W38700934 @default.
• W3178268080 cites W770013183 @default.
• W3178268080 doi "https://doi.org/10.1016/j.asoc.2021.107688" @default.
• W3178268080 hasPublicationYear "2021" @default.
• W3178268080 type Work @default.
• W3178268080 sameAs 3178268080 @default.
• W3178268080 citedByCount "13" @default.
• W3178268080 countsByYear W31782680802020 @default.
• W3178268080 countsByYear W31782680802021 @default.
• W3178268080 countsByYear W31782680802022 @default.
• W3178268080 countsByYear W31782680802023 @default.
• W3178268080 crossrefType "journal-article" @default.
• W3178268080 hasAuthorship W3178268080A5004385039 @default.
• W3178268080 hasAuthorship W3178268080A5005078316 @default.
• W3178268080 hasAuthorship W3178268080A5074492402 @default.
• W3178268080 hasAuthorship W3178268080A5081436755 @default.
• W3178268080 hasAuthorship W3178268080A5083106608 @default.
• W3178268080 hasAuthorship W3178268080A5091376805 @default.
• W3178268080 hasBestOaLocation W31782680802 @default.
• W3178268080 hasConcept C101468663 @default.
• W3178268080 hasConcept C111919701 @default.
• W3178268080 hasConcept C119857082 @default.
• W3178268080 hasConcept C127413603 @default.
• W3178268080 hasConcept C154945302 @default.
• W3178268080 hasConcept C159149176 @default.
• W3178268080 hasConcept C166957645 @default.
• W3178268080 hasConcept C199505168 @default.
• W3178268080 hasConcept C201995342 @default.
• W3178268080 hasConcept C2778049539 @default.
• W3178268080 hasConcept C2780451532 @default.
• W3178268080 hasConcept C41008148 @default.
• W3178268080 hasConcept C79581498 @default.
• W3178268080 hasConcept C90509273 @default.
• W3178268080 hasConcept C95457728 @default.
• W3178268080 hasConcept C98045186 @default.
• W3178268080 hasConceptScore W3178268080C101468663 @default.
• W3178268080 hasConceptScore W3178268080C111919701 @default.
• W3178268080 hasConceptScore W3178268080C119857082 @default.
• W3178268080 hasConceptScore W3178268080C127413603 @default.
• W3178268080 hasConceptScore W3178268080C154945302 @default.
• W3178268080 hasConceptScore W3178268080C159149176 @default.
• W3178268080 hasConceptScore W3178268080C166957645 @default.
• W3178268080 hasConceptScore W3178268080C199505168 @default.
• W3178268080 hasConceptScore W3178268080C201995342 @default.
• W3178268080 hasConceptScore W3178268080C2778049539 @default.
• W3178268080 hasConceptScore W3178268080C2780451532 @default.
• W3178268080 hasConceptScore W3178268080C41008148 @default.
• W3178268080 hasConceptScore W3178268080C79581498 @default.
• W3178268080 hasConceptScore W3178268080C90509273 @default.
• W3178268080 hasConceptScore W3178268080C95457728 @default.
• W3178268080 hasConceptScore W3178268080C98045186 @default.
• W3178268080 hasLocation W31782680801 @default.
• W3178268080 hasLocation W31782680802 @default.
• W3178268080 hasLocation W31782680803 @default.
• W3178268080 hasLocation W31782680804 @default.
• W3178268080 hasOpenAccess W3178268080 @default.

• next