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Winner-take-all in action selection
Winner-take-all is a computer science concept that has been widely applied in behavior-based robotics as a method of action selection for intelligent agents. Winner-take-all systems work by connecting modules (task-designated areas) in such a way that when one action is performed it stops all other actions from being performed, so only one action is occurring at a time. The name comes from the idea that the "winner" action takes all of the motor system's power.〔Schilling, M., Paskarbeit, J., Hoinville, T., Hüffmeier, A., Schneider, A., Schmitz, J., Cruse, H. (Sept. 17 2013). A hexapod walker using a heterarchical structure for action selection. Frontiers in Computational Neuroscience, 7. doi: 10.3389/fncom.2013.00126〕〔Öztürk, P. (2009). Levels and types of action selection: The action selection soup. Adaptive Behavior, 17. doi: 10.1177/1059712309339854〕〔Koch, C., Ullman, S. (1985). Shifts in selective visual attention: Towards the underlying neural circuitry. Retrieved from ().〕
== History ==
In the 1980s and 1990s, many roboticists and cognitive scientists were attempting to find speedier and more efficient alternatives to the traditional world modeling method of action selection.〔Jones, J.L. (2004). Robot programming: A practical guide to behavior-based robotics. The McGraw Hill Companies, Inc.〕 In 1982, Jerome A. Feldman and D.H. Ballard published the "Connectionist Models and Their Properties", referencing and explaining winner-take-all as a method of action selection. Feldman's architecture functioned on the simple rule that in a network of interconnected action modules, each module will set its own output to zero if it reads a higher input than its own in any other module.〔Ballard, D.H., Feldman, J.A. (1982). Connectionist models and their properties. Cognitive Science, 6, 205-54.〕 In 1986, Rodney Brooks introduced behavior-based artificial intelligence. Winner-take-all architectures for action selection soon became a common feature of behavior-based robots, because selection occurred at the level of the action modules (bottom-up) rather than at a separate cognitive level (top-down), producing a tight coupling of stimulus and reaction.〔Brooks, R.A. (1986). A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, 2, 14-23. Retrieved from ().〕
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