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![]() Title:Flexible Risk Aware Sequential Decision Making Authors:Nadjet Bourdache Conference:SUM 2024 Tags:Decision theory under risk, Markov decision processes, Preference modeling, Preference modeling. and Sequential decision making Abstract: In this work, we study risk aware sequential decision making in a Markov Decision Process (MDP). Unlike many works in the literature, where MDPs are solved by optimizing expected rewards (ER), and thus assuming neutrality w.r.t. risk, we use a more sophisticated operator: the Weighted Ordered Weighted Average (WOWA), a parameterized operator that allows to model a wide range of behaviors, from extreme risk seeking to extreme risk aversion (as well as compromises between both behaviors). This operator has thus a high descriptive capacity, but is rather difficult to optimize in an MDP because of its non-linearity that makes standard solving algorithms sub-optimal. In this paper, we introduce and justify a ranking algorithm that allows to determine an optimal (or nearly optimal) policy for a wide range of attitudes w.r.t. risk (averse, seeking, neutral, intermediate) using WOWA. Empirical results are given to illustrate the relevance and the efficiency of the approach. Flexible Risk Aware Sequential Decision Making ![]() Flexible Risk Aware Sequential Decision Making | ||||
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