Risk-sensitive decision-theoretic diagnosis

Decision-theoretic Planning under Risk-sensitive Planning Objectives

Game-theoretic approach to risk-sensitive benchmarked asset management

In this article we consider a game theoretic approach to the Risk-Sensitive Benchmarked Asset Management problem (RSBAM) of Davis and Lleo [6]. In particular, we consider a stochastic differential game between two players, namely, the investor who has a power utility while the second player represents the market which tries to minimize the expected payoff of the investor. The market does this b...

مقایسه روش‌های مختلف یادگیری ماشین در تشخیص پرفشاری خون در بیماران دیابتی با و بدون در نظر گرفتن هزینه‌ها

Background and Objectives: Diabetic patients are always at risk of hypertension. In this paper, the main goal was to design a native cost sensitive model for the diagnosis of hypertension among diabetics considering the prior probabilities. Methods: In this paper, we tried to design a cost sensitive model for the diagnosis of hypertension in diabetic patients, considering the distribution of...

Risk-Sensitive Decision-Theoretic Troubleshooting

We study the problem of sequencing tests for the discovery of a faulty component, e.g., in a telecommunications network, where there is a random cost associated with testing a component. A novel feature in our approach is that a risk-sensitive performance criterion is used in order to rank diierent competing schedules.

Existence and Finiteness Conditions for Risk-Sensitive Planning: First Results

Decision-theoretic planning with risk-sensitive planning objectives is important for building autonomous agents or decisionsupport agents for real-world applications. However, this line of research has been largely ignored in the artificial intelligence and operations research communities since planning with risksensitive planning objectives is much more complex than planning with risk-neutral ...

Existence and Finiteness Conditions for Risk-Sensitive Planning: Results and Conjectures

Decision-theoretic planning with risk-sensitive planning objectives is important for building autonomous agents or decision-support systems for real-world applications. However, this line of research has been largely ignored in the artificial intelligence and operations research communities since planning with risk-sensitive planning objectives is more complicated than planning with risk-neutra...