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dc.contributor.authorOlivier, Paul
dc.contributor.authorMoreno Aróstegui, Juan Manuel
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.date.accessioned2014-01-03T11:53:56Z
dc.date.created2013
dc.date.issued2013
dc.identifier.citationOlivier, P.; Moreno, J. The imbalance network and incremental evolution for mobile robot nervous system design. A: International Conference on Artificial Neural Networks. "23rd International Conference on Artificial Neural Networks, ICANN 2013". Sofia: 2013, p. 519-526.
dc.identifier.isbn9783642407277
dc.identifier.urihttp://hdl.handle.net/2117/21143
dc.description.abstractAutomatic design of neurocontrollers (as in Evoluationary Robotics) utilizes incremental evolution to solve for more complex behaviors. Also manual design techniques such as task decomposition are employed. Manual design itself can benefit from focusing on using incremental evolution to add more automatic design. The imbalance network is a neural network that integrates incremental evolution with an incremental design process without the need for task decomposition. Instead, the imbalance network uses the mechanism of the equilibrium-action cycle to structure the network while emphasizing behavior emergence. An example 11-step design (including a 5-step evolutionary process) is briefly mentioned to help ground the imbalance network concepts.
dc.format.extent8 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica::Robòtica
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.lcshXarxes neuronals (Informàtica)
dc.subject.otherimbalance network
dc.subject.otherequilibrium-action cycle
dc.subject.otherincremental evolution
dc.subject.otheremergence
dc.subject.othertask decomposition.
dc.titleThe imbalance network and incremental evolution for mobile robot nervous system design
dc.typeConference report
dc.subject.lemacXarxes neuronals (Informàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. AHA - Arquitectures Hardware Avançades
dc.identifier.doi10.1007/978-3-642-40728-4_65
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://download.springer.com/static/pdf/77/chp%253A10.1007%252F978-3-642-40728-4_65.pdf?auth66=1388922366_7544ba391bf713481c72dd5cf8f39169&ext=.pdf
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac12881317
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorOlivier, P.; Moreno, J.
local.citation.contributorInternational Conference on Artificial Neural Networks
local.citation.pubplaceSofia
local.citation.publicationName23rd International Conference on Artificial Neural Networks, ICANN 2013
local.citation.startingPage519
local.citation.endingPage526


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