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SME: Learning automata-based algorithm for estimating the mobility model of soccer players

Jamalian, A. H ; Sharif University of Technology | 2007

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  1. Type of Document: Article
  2. DOI: 10.1109/COGINF.2007.4341925
  3. Publisher: 2007
  4. Abstract:
  5. Soccer model and relation of players and coach has been analyzed by a learning automata-based method, called Soccer Mobility Estimator (SME), who estimates the mobility model of soccer players. During a soccer match, players play according to a certain program designed by coach. The pattern of players' mobility is not stochastic and it can be assumed that they are playing with a certain mobility model. Since knowledge about mobility model of nodes in mobile ad-hoc networks has a substantial effect on its performance evaluation, knowledge about mobility model of soccer players can be useful for coaches and experts for game analysis. In fact the mobility model of players could be an important parameter for assessment of team solidarity. Simulation results show that the mobility model of soccer players is similar, up to 66%, to the RPGM (Reference Point Group Mobility) mobility model. ©2007 IEEE
  6. Keywords:
  7. Ad hoc networks ; Estimation ; Learning algorithms ; Stochastic programming ; Translation (languages) ; Wireless telecommunication systems ; Cognitive informatics ; Game analysis ; Group mobility ; International conferences ; Learning automata ; Learning automaton ; Mobile Ad-Hoc Networks ; Mobility model ; Mobility modeling ; Performance evaluation ; Reference point ; RPGM ; Simulation results ; SME ; Soccer analysis ; Soccer players ; Stochastic models
  8. Source: 6th IEEE International Conference on Cognitive Informatics, ICCI 2007, Lake Tahoe, CA, 6 August 2007 through 8 August 2007 ; October , 2007 , Pages 462-469 ; 1424413273 (ISBN); 9781424413270 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4341925