In many applications there are critical states that might harm the agent or the environment and should therefore be avoided. In practice, those states are often ...
In many applications there are critical states that might harm the agent or the environment and should therefore be avoided. In practice, those states are often ...
Decision making based on Markov decision processes (MDPs) is an emerging research area as MDPs provide a convenient formalism to learn an optimal behavior ...
In this article, we review the scholarly literature on multinational managerial decision making, global outsourcing and organizational effectiveness and the ...
Markov decision processes (MDPs) provide a mathematical framework for modeling sequential decision making where system evolution and cost/reward depend on ...
Apr 20, 2024 · Abstract—This paper studies a risk-sensitive decision-making problem under uncertainty. It considers a decision-making pro-.
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Jun 26, 2023 · This differs from human decision-making, where gains and losses are valued differently and outlying outcomes are given increased consideration.
Apr 20, 2024 · This paper studies a risk-sensitive decision-making problem under uncertainty. It considers a decision-making process that unfolds over a ...
Risk-sensitive decision-making is crucial in practical applications, particularly in revenue management. A pure focus on optimizing expected rewards can be ...
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Abstract. In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or ...