Comparing a brain-inspired robot action selection mechanism with 'winner-takes-all'

2002 ◽  
Keyword(s):  
Action Selection ◽  
Selection Mechanism ◽  
Winner Takes All

scholarly journals STATE MACHINE MODEL OF HYPOTHESIZED VOLUNTARY ACTION SELECTION MECHANISM OF SUBSTANTIA NIGRA PARS COMPACTA AND LOCUS COERULEUS

2019 ◽  
Author(s):  
Christopher Rourk
Keyword(s):  
Electron Transport ◽  
Substantia Nigra ◽  
Action Selection ◽  
Neural Correlates ◽  
State Machine ◽  
Voluntary Action ◽  
Substantia Nigra Pars Compacta ◽  
Selection Mechanism ◽  
Machine Model ◽  
Apparent Ability

A hypothesized voluntary action selection mechanism for the SNc and LC has been proposed that is based on the apparent ability of ferritin and neuromelanin to support electron transport in those tissues. (Rourk 2018; Rourk 2019). A state machine model is presented in this paper that provides an explanation for neural correlates of that hypothesized voluntary action selection mechanism to the human experience of consciousness.

scholarly journals AIN-Based Action Selection Mechanism for Soccer Robot Systems

2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
Yin-Tien Wang ◽  
Zhi-Jun You ◽  
Chia-Hsing Chen
Keyword(s):  
Adaptive Immune System ◽  
Role Playing ◽  
Action Selection ◽  
Selection Mechanism ◽  
Soccer Robot ◽  
Soccer Game ◽  
Artificial Immune Network ◽  
Robot Systems ◽  
Simulation And Experiment ◽  
Soccer Team

Role and action selections are two major procedures of the game strategy for multiple robots playing the soccer game. In role-select procedure, a formation is planned for the soccer team, and a role is assigned to each individual robot. In action-select procedure, each robot executes an action provided by an action selection mechanism to fulfill its role playing. The role-select procedure was often designed efficiently by using the geometry approach. However, the action-select procedure developed based on geometry approach will become a very complex task. In this paper, a novel action-select algorithm for soccer robots is proposed by using the concepts of artificial immune network (AIN). This AIN-based action-select provides an efficient and robust algorithm for robot role selection. Meanwhile, a reinforcement learning mechanism is applied in the proposed algorithm to enhance the response of the adaptive immune system. Simulation and experiment are carried out to verify the proposed AIN-based algorithm, and the results show that the proposed algorithm provides an efficient and applicable algorithm for mobile robots to play soccer game.

scholarly journals Biologically constrained action selection improves cognitive control in a model of the Stroop task

2007 ◽  
Vol 362 (1485) ◽  
pp. 1671-1684 ◽  
Author(s):  
Tom Stafford ◽  
Kevin N Gurney
Keyword(s):  
Cognitive Control ◽  
Diffusion Model ◽  
Stroop Task ◽  
Response Selection ◽  
Action Selection ◽  
Selection Mechanism ◽  
Choice Behaviour ◽  
Adaptive Action ◽  
Final Response ◽  
Constrained Solutions

The Stroop task is a paradigmatic psychological task for investigating stimulus conflict and the effect this has on response selection. The model of Cohen et al. (Cohen et al . 1990 Psychol. Rev. 97 , 332–361) has hitherto provided the best account of performance in the Stroop task, but there remains certain key data that it fails to match. We show that this failure is due to the mechanism used to perform final response selection—one based on the diffusion model of choice behaviour (Ratcliff 1978 Psychol. Rev. 85 , 59–108). We adapt the model to use a selection mechanism which is based on the putative human locus of final response selection, the basal ganglia/thalamo-cortical complex (Redgrave et al. 1999 Neuroscience 89 , 1009–1023). This improves the match to the core human data and, additionally, makes it possible for the model to accommodate, in a principled way, additional mechanisms of cognitive control that enable better fits to the data. This work prompts a critique of the diffusion model as a mechanism of response selection, and the features that any response mechanism must possess to provide adaptive action selection. We conclude that the consideration of biologically constrained solutions to the action selection problem is vital to the understanding and improvement of cognitive models of response selection.

Local resource depletion hypothesis as a mechanism for action selection in the brain

2013 ◽  
Vol 36 (6) ◽  
pp. 682-683 ◽  
Author(s):  
Aneta Brzezicka ◽  
Jan Kamiński ◽  
Andrzej Wróbel
Keyword(s):  
Opportunity Cost ◽  
Cost Model ◽  
Resource Depletion ◽  
Action Selection ◽  
Alternative View ◽  
Selection Mechanism ◽  
Local Resource ◽  
Competition Theory ◽  
The Brain ◽  
Neural Competition

AbstractAs a comment on Kurzban et al.'s opportunity cost model, we propose an alternative view of mental effort and the action selection mechanism in the brain. Our hypothesis utilizes local resource depletion within neuronal networks, which justifies from a neurophysiological perspective why mental fatigue diminishes after switching to a novel task and explains action selection by means of neural competition theory.

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