Based on the research done in the last decade attempts have been made to propose descrip tion logics as unifying formalisms for the var ious class based representation languages used in di erent areas These attempts have made apparent that sound complete and decidable description logics still su er from several lim itations regarding modeling classes of aggre gate objects expressing general inc...

In the best case using an abstraction hierarchy in problem solving can yield an exponential speed up in search e ciency Such a speed up is predicted by var ious analytical models developed in the literature and e ciency gains of this order have been con rmed empir ically However these models assume that the Down ward Re nement Property DRP holds When this property holds backtracking never need ...

Abstract Safety is critical to broadening the real-world use of reinforcement learning. Modeling safety aspects using a safety-cost signal separate from reward and bounding expected becoming standard practice, since it avoids problem finding good balance between performance. However, can be risky set constraints only on expectation neglecting tail distribution, which might have prohibitively la...

Classical formulations of the portfolio optimization problem, such as mean-variance or Value-at-Risk (VaR) approaches, can result in a portfolio extremely sensitive to errors in the data, such as mean and covariance matrix of the returns. In this paper we propose a way to alleviate this problem in a tractable manner. We assume that the distribution of returns is partially known, in the sense th...

In this paper, we assess the magnitude of model uncertainty of credit risk portfolio models, i.e., what is the maximum and minimum Value-at-Risk (VaR) that can be justified given a certain amount of available information. Puccetti and Rüschendorf (2012b) and Embrechts et al. (2013) propose the rearrangement algorithm (RA) as a general method to approximate VaR bounds when the default probabilit...

Recent literature has investigated the risk aggregation of a portfolio X = (Xi)1≤i≤n under the sole assumption that the marginal distributions of the risks Xi are specified but not their dependence structure. There exists a range of possible values for any risk measure of S = ∑n i=1Xi and the dependence uncertainty spread, as measured by the difference between the upper bound and the lower boun...

4 We present a systematic framework to manage conflicts among multiple decision makers (stake5 holders) arising in the multiobjective design and operations of process systems. Addressing such 6 situations is particularly relevant in sustainability studies because many conflicting social, envi7 ronmental, and economic objectives need to considered. The proposed framework factors in the 8 opinion...

In this paper we address the problem of decision making within a Markov de-cision process (MDP) framework where risk and modeling errors are taken intoaccount. Our approach is to minimize a risk-sensitive conditional-value-at-risk(CVaR) objective, as opposed to a standard risk-neutral expectation. We refer tosuch problem as CVaR MDP. Our first contribution is to show that a CVaR...

A distortion risk measure used in finance and insurance is defined as the expected value of potential loss under a scenario probability measure. In this paper, the tail distortion risk measure is introduced to assess tail risks of excess losses modeled by the right tails of loss distributions. The asymptotic linear relation between tail distortion and Value-at-Risk is derived for heavy tailed l...