Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Mehdi Keramati"'
Publikováno v:
Nature Communications, Vol 10, Iss 1, Pp 1-14 (2019)
The reinforcement learning literature suggests decisions are based on a model-free system, operating retrospectively, and a model-based system, operating prospectively. Here, the authors show that a model-based retrospective inference of a reward’s
Externí odkaz:
https://doaj.org/article/ca9bae169c454436895a7d3764634701
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 1, p e1008552 (2021)
Dual-reinforcement learning theory proposes behaviour is under the tutelage of a retrospective, value-caching, model-free (MF) system and a prospective-planning, model-based (MB), system. This architecture raises a question as to the degree to which,
Externí odkaz:
https://doaj.org/article/ec944fa9d760448daad32d499892ff47
Publikováno v:
PLoS Computational Biology, Vol 15, Iss 3, p e1006827 (2019)
Evaluating the future consequences of actions is achievable by simulating a mental search tree into the future. Expanding deep trees, however, is computationally taxing. Therefore, machines and humans use a plan-until-habit scheme that simulates the
Externí odkaz:
https://doaj.org/article/3dff8440bddb4c299f2ade1f819b2d7f
Autor:
Nitzan Shahar, Tobias U Hauser, Michael Moutoussis, Rani Moran, Mehdi Keramati, NSPN consortium, Raymond J Dolan
Publikováno v:
PLoS Computational Biology, Vol 15, Iss 2, p e1006803 (2019)
A well-established notion in cognitive neuroscience proposes that multiple brain systems contribute to choice behaviour. These include: (1) a model-free system that uses values cached from the outcome history of alternative actions, and (2) a model-b
Externí odkaz:
https://doaj.org/article/89a0752e61d24bfabd6516f692dbec17
Publikováno v:
PLoS ONE, Vol 13, Iss 4, p e0195399 (2018)
Every day we make choices under uncertainty; choosing what route to work or which queue in a supermarket to take, for example. It is unclear how outcome variance, e.g. uncertainty about waiting time in a queue, affects decisions and confidence when o
Externí odkaz:
https://doaj.org/article/835b53b4456c4948b79e0ea8f7c8e595
Autor:
Julie J Lee, Mehdi Keramati
Publikováno v:
PLoS Computational Biology, Vol 13, Iss 9, p e1005753 (2017)
Decision-making in the real world presents the challenge of requiring flexible yet prompt behavior, a balance that has been characterized in terms of a trade-off between a slower, prospective goal-directed model-based (MB) strategy and a fast, retros
Externí odkaz:
https://doaj.org/article/704f241b4f3d4611924681fa30818e09
Autor:
Mehdi Keramati, Boris Gutkin
Publikováno v:
eLife, Vol 3 (2014)
Efficient regulation of internal homeostasis and defending it against perturbations requires adaptive behavioral strategies. However, the computational principles mediating the interaction between homeostatic and associative learning processes remain
Externí odkaz:
https://doaj.org/article/6665c525c9c94da2a1505fcac1b89f48
Autor:
Mehdi Keramati, Boris Gutkin
Publikováno v:
PLoS ONE, Vol 8, Iss 4, p e61489 (2013)
Despite explicitly wanting to quit, long-term addicts find themselves powerless to resist drugs, despite knowing that drug-taking may be a harmful course of action. Such inconsistency between the explicit knowledge of negative consequences and the co
Externí odkaz:
https://doaj.org/article/a488a84bff724d76b36d0ac35af82914
Publikováno v:
PLoS Computational Biology, Vol 7, Iss 5, p e1002055 (2011)
Instrumental responses are hypothesized to be of two kinds: habitual and goal-directed, mediated by the sensorimotor and the associative cortico-basal ganglia circuits, respectively. The existence of the two heterogeneous associative learning mechani
Externí odkaz:
https://doaj.org/article/1fa231b1583344fca7d94b8c5fea176d
Non-intrusive load monitoring (NILM) as the process of extracting the usage pattern of appliances from the aggregated power signal is among successful approaches aiding residential energy management. In recent years, high volume datasets on power pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d12efdbb4655754c2809780b4969d099
