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Dysfunctional reward processing amplifies stress-related smartphone overuse: Evidence from ERPs and ecological momentary assessment. [PDF]
Qi H +6 more
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Electrophysiological Correlates of Reward Processing in the Human Ventral Tegmental Area
Ramaswamy A +9 more
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Reward revision and the average reward markov decision process
Operations-Research-Spektrum, 1987We integrate two numerical procedures for solving the average reward Markov decision process (MDP), standard successive approximations and modified policy iteration with reward revision. Reward revision is the process of revising the reward structure of a second, more computationally desirable MDP so as to produce, in the limit, an optimality equation ...
White, C. C. III, Scherer, W. T.
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Reward and Punishment Processing in Depression
Biological Psychiatry, 2010Depression is a complex and heterogeneous disorder whose cause is poorly understood. Theories on the mechanisms of the disease have often focused on either its neurobiology or its cognitive and behavioral manifestations. Recently, studies exploring how depressed patients process reward and punishment have linked these two facets together.
Neir, Eshel, Jonathan P, Roiser
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Reward processing in anorexia nervosa
Neuropsychologia, 2012Individuals with anorexia nervosa (AN) demonstrate a relentless engagement in behaviors aimed to reduce their weight, which leads to severe underweight status, and occasionally death. Neurobiological abnormalities, as a consequence of starvation are controversial: evidence, however, demonstrates abnormalities in the reward system of patients, and ...
Keating, Charlotte +4 more
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Processed foods and food reward
Science, 2019Processed foods compromise the fidelity of gut-brain signaling of food ...
Dana M, Small +1 more
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Reward processes with nonlinear reward functions
Journal of Applied Probability, 1996Based on a semi-Markov process J(t), t ≧ 0, a reward process Z(t), t ≧ 0, is introduced where it is assumed that the reward function, p(k, x) is nonlinear; if the reward function is linear, i.e. ρ (k, x) = kx, the reward process Z(t), t ≧ 0, becomes the classical one, which has been considered by many authors.
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Markov Decision Processes with Arbitrary Reward Processes
Mathematics of Operations Research, 2008We consider a learning problem where the decision maker interacts with a standard Markov decision process, with the exception that the reward functions vary arbitrarily over time. We show that, against every possible realization of the reward process, the agent can perform as well—in hindsight—as every stationary policy. This generalizes the classical
Jia Yuan Yu, Shie Mannor, Nahum Shimkin
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