Results 241 to 250 of about 95,161 (264)

GABAB Receptors in Reward Processes

2010
gamma-aminobutyric acid (GABA) is the predominant inhibitory neurotransmitter in the brain which acts through different receptor subtypes. Metabotropic GABA(B) receptors are widely distributed throughout the brain. Alterations in GABA signaling through pharmacological activation or deactivation of the GABA(B) receptor regulate behavior and brain reward
Styliani, Vlachou, Athina, Markou
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Asymptotics for renewal-reward processes with retrospective reward structure

Operations Research Letters, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Prediction for Reward Processes

Stochastic Models, 2010
We consider D(t) = [J(t), X(t), Z ρ(t)], t ≥ 0, where J(t) is a semi-Markov process, X(t) is the age process for J(t), and Z ρ(t) is a reward process on J(t). In this article we produce a prediction formula to predict Z ρ(t + s) based on the history (t), the σ-field generated by {D(u), u ≤ t}. In addition, we derive the conditional distribution of the
A. R. Soltani, K. Khorshidian, A. Ghafaripour   +2 more
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Renewal Reward Process With Uncertain Interarrival Times and Random Rewards

IEEE Transactions on Fuzzy Systems, 2018
Renewal reward process is used to measure the cumulative occasional rewards up to some given time. So far, two basic types of renewal reward processes with only random parameters or with only uncertain parameters have been proposed. This paper aims at proposing a new type of renewal reward process, which has uncertain interarrival times and random ...
Kai Yao 0002, Jian Zhou 0003
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Semi-Regenerative Processes with Unbounded Rewards

Mathematics of Operations Research, 1979
A semi-regenerative process (SRP) is combined with a reward structure such that the accumulated reward during [0, t] is the sum of a functional of the SRP and a functional of the embedded Markov renewal process (MRP). For the expected (discounted) return a Markov renewal equation (MRE) is given.
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RENEWAL REWARD PROCESSES

1969
Abstract : The paper considers a process in which rewards are being earned and for which there exist time points at which the process begins anew--that is, that there exists an embedded renewal process. An expression for the asymptotic mean reward earned during any time interval is then obtained.
Sheldon M. Ross, Mark Brown
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Adaptive Optimization of Markov Reward Processes

Proceedings of the 44th IEEE Conference on Decision and Control, 2006
We consider the problem of optimizing the average reward of Markov chains controlled by two sets of parameters 1) a set of tunable parameters and 2) a set of fixed but unknown parameters. We study the convergence characteristics of recursive estimation procedures based on the observation of regenerative cycles. We also provide sufficient conditions for
Enrique Campos-Náñez, Stephen D. Patek
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Markov Reward Processes

2010
In this chapter, we consider reward processes of an irreducible continuous-time block-structured Markov chain. By using the RG-factorizations, we provide a unified algorithmic framework to derive expressions for conditional distributions and conditional moments of the reward processes.
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Process, Result and Reward

1998
In the last chapter we saw how the idea of a code of practice or statement of values had inbuilt problems — unless it is conceived as part of a larger scale process it is unlikely to help in creating the opportunities for individuals to identify points of contact between their own value systems and what is being advanced within the code.
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Reward processing as a common diathesis for chronic pain and depression

Neuroscience and Biobehavioral Reviews, 2021
Tim V Salomons, Wiebke Gandhi, Sakina J Rizvi   +2 more
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