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Electrophysiological Correlates of Reward Processing in the Human Ventral Tegmental Area

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Ramaswamy A   +9 more
europepmc   +1 more source
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Reward revision and the average reward markov decision process

Operations-Research-Spektrum, 1987
We 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.
openaire   +2 more sources

Reward and Punishment Processing in Depression

Biological Psychiatry, 2010
Depression 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
openaire   +2 more sources

Reward processing in anorexia nervosa

Neuropsychologia, 2012
Individuals 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
openaire   +5 more sources

Processed foods and food reward

Science, 2019
Processed foods compromise the fidelity of gut-brain signaling of food ...
Dana M, Small   +1 more
openaire   +2 more sources

Reward processes with nonlinear reward functions

Journal of Applied Probability, 1996
Based 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.
openaire   +1 more source

Markov Decision Processes with Arbitrary Reward Processes

Mathematics of Operations Research, 2008
We 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
openaire   +2 more sources

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