2008
DOI: 10.1016/j.neunet.2007.09.016
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SOVEREIGN: An autonomous neural system for incrementally learning planned action sequences to navigate towards a rewarded goal

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Cited by 35 publications
(18 citation statements)
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References 76 publications
(78 reference statements)
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“…The M representations include cortical and cerebellar circuits that control discrete adaptive responses (Evarts, 1973 ; Ito, 1984 ; Kalaska, Cohen, Hyde, & Prud’homme, 1989 ; Thompson, 1988 ). More complete models of the internal structure of these several types of representations have been presented elsewhere (e.g., Brown, Bullock, & Grossberg, 2004 ; Bullock, Cisek, & Grossberg, 1998 ; Carpenter & Grossberg, 1991 ; Contreras-Vidal, Grossberg, & Bullock, 1997 ; Dranias, Grossberg, & Bullock, 2008 ; Fiala, Grossberg, & Bullock, 1996 ; Gnadt & Grossberg, 2008 ; Grossberg, 1987 ; Grossberg, Bullock & Dranias, 2008 ; Grossberg & Merrill, 1996 ; Grossberg & Schmajuk, 1987 ; Raizada & Grossberg, 2003 ), and can be incorporated into future elaborations of nSTART without undermining any of the current model's conclusions.
Fig.
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Section: Methodsmentioning
confidence: 99%
“…The M representations include cortical and cerebellar circuits that control discrete adaptive responses (Evarts, 1973 ; Ito, 1984 ; Kalaska, Cohen, Hyde, & Prud’homme, 1989 ; Thompson, 1988 ). More complete models of the internal structure of these several types of representations have been presented elsewhere (e.g., Brown, Bullock, & Grossberg, 2004 ; Bullock, Cisek, & Grossberg, 1998 ; Carpenter & Grossberg, 1991 ; Contreras-Vidal, Grossberg, & Bullock, 1997 ; Dranias, Grossberg, & Bullock, 2008 ; Fiala, Grossberg, & Bullock, 1996 ; Gnadt & Grossberg, 2008 ; Grossberg, 1987 ; Grossberg, Bullock & Dranias, 2008 ; Grossberg & Merrill, 1996 ; Grossberg & Schmajuk, 1987 ; Raizada & Grossberg, 2003 ), and can be incorporated into future elaborations of nSTART without undermining any of the current model's conclusions.
Fig.
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Section: Methodsmentioning
confidence: 99%
“…We also would like to highlight the differences between our contribution and those presented in SOVEREIGN [1]. The authors of that study modeled a neural network that was based on characteristics of the animals' visual apparatus.…”
Section: Controller and Behaviormentioning
confidence: 96%
“…Traditionally, the problem of synthetic vision of autonomous agents (robots and virtual characters) has been approached with attempts to build models capable of preprocessing the sensor signals and drive the motor actions of the agents [1,2]. Another line of investigation tries to work with internal mental maps that represent the character's environment, where calculations can be made so that the agent can guide itself through the world.…”
Section: Introductionmentioning
confidence: 99%
“…Embodied agents need to be able to autonomously and adaptively interact with their environment. Grossberg presents a large-scale visuomotor architecture: the Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation model (SOVEREIGN; Gnadt and Grossberg, 2008). This architecture consists of several sensory, motor and memory components and is able to perform motor sequences under different motivational states as well as to learn more efficient sequences in response to rewards.…”
Section: Embodied Sensorimotor Systemsmentioning
confidence: 99%