2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) 2017
DOI: 10.1109/devlrn.2017.8329816
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Abstract: The use of biologically realistic (brain-like) control systems in autonomous robots offers two potential benefits. For neuroscience, it may provide important insights into normal and abnormal control and decision-making in the brain, by testing whether the computational learning and decision rules proposed on the basis of simple laboratory experiments lead to effective and coherent behaviour in complex environments. For robotics, it may offer new insights into control system designs, for example in the context… Show more

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Cited by 2 publications
(2 citation statements)
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“…More broadly, cognitive processes are built atop a hierarchy that involves multiple facilitative interactions between layers. Although such an architecture seems complex, computationally it is highly efficient (Piccolo et al, 2018;Lee et al, 2019). For instance, exposure to an unexpected pain stimulus recruits the innate and Pavlovian systems first, to provide rapid, safe defense using evolutionarily learned information.…”
Section: Conscious Pain Perception and Interactions Between Controllersmentioning
confidence: 99%
“…More broadly, cognitive processes are built atop a hierarchy that involves multiple facilitative interactions between layers. Although such an architecture seems complex, computationally it is highly efficient (Piccolo et al, 2018;Lee et al, 2019). For instance, exposure to an unexpected pain stimulus recruits the innate and Pavlovian systems first, to provide rapid, safe defense using evolutionarily learned information.…”
Section: Conscious Pain Perception and Interactions Between Controllersmentioning
confidence: 99%
“…Each system is best in different situations: the innate/Pavlovian systems exploits evolutionarily learned knowledge and allow rapid responses before much learning has happened, in effect providing an evolutionary prior on action space. Goal-directed learning allow sophisticated modelling of the world, supporting planning and flexibility [49]. And habit learning provides stability in the face of inherent unpredictability and over extended time, alongside considerable computational efficiency [50].…”
Section: Multiple Controller Architecturesmentioning
confidence: 99%