Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/43335
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dc.titleContinuous-spaced action selection for single- and multi-robot tasks using cooperative extended Kohonen maps
dc.contributor.authorLow, K.H.
dc.contributor.authorLeow, W.K.
dc.contributor.authorAng Jr., M.H.
dc.date.accessioned2013-07-23T09:31:17Z
dc.date.available2013-07-23T09:31:17Z
dc.date.issued2004
dc.identifier.citationLow, K.H.,Leow, W.K.,Ang Jr., M.H. (2004). Continuous-spaced action selection for single- and multi-robot tasks using cooperative extended Kohonen maps. Conference Proceeding - IEEE International Conference on Networking, Sensing and Control 1 : 198-203. ScholarBank@NUS Repository.
dc.identifier.isbn0780381939
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/43335
dc.description.abstractAction selection is a central issue in the design of behavior-based control architectures for autonomous mobile robots. This paper presents an action selection framework based on an assemblage of self-organizing neural networks called Cooperative Extended Kohonen Maps. This framework encapsulates two features that significantly enhance a robot's action selection capability: self-organization in the continuous state and action spaces to provide smooth, efficient and fine motion control; action selection via the cooperation and competition of Extended Kohonen Maps so that more complex motion tasks can be achieved. Qualitative and quantitative comparisons for both single- and multi-robot motion tasks show that our framework can provide better action selection than do action superposition methods.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.sourcetitleConference Proceeding - IEEE International Conference on Networking, Sensing and Control
dc.description.volume1
dc.description.page198-203
dc.identifier.isiutNOT_IN_WOS
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