In multi-objective reinforcement learning (MORL), much attention is paid to generating optimal solution sets for unknown utility functions of users, based on the stochastic reward vectors only. In online MORL on the other hand, the agent will often be able to elicit preferences from the user, enabling it to learn about the utility function of its user directly. In this paper, we study online MO...

Shafer's theory of belief and the Bayesian theory of probability are two alternative and mutually inconsistent approaches toward modelling uncertainty in artificial in­ telligence. To help reduce the conflict between these two approaches, this paper reexammes expected utility theory from which Bayesian probability theory is derived. Expected utility theory req mres the decision maker to ass1gn ...

Metal price is one of the most important parameters in the calculation of cut- off grade. The cut- off grade has the main role in determination of mine layout. Mine layout actuates mineable reserve, mine life and economic profitability. Not considering the uncertainty in metal prices can lead to a non-optimal layout. In this paper optimum underground mine layout is determined by expected utilit...

We give here a comparison of the expected outcome theory, the expected utility theory, and the Bayesian decision theory, by way of a simple numerical toy problem in which we look at the investment willingness to avert a high impact low probability event. It will be found that for this toy problem the modeled investment willingness under the Bayesian decision theory is minimally three times high...

In recent years portfolio optimization models that consider more criteria than the standard expected return and variance objectives of the Markowitz model have become popular. For such models, two approaches to find a suitable portfolio for an individual investor are possible. In the multiattribute utility theory (MAUT) approach a utility function is constructed based on the investor’s preferen...

In interactive multi-objective reinforcement learning (MORL), an agent has to simultaneously learn about the environment and preferences of user, in order quickly zoom on those decisions that are likely be preferred by user. this paper we study MORL context multi-armed bandits. Contrary earlier approaches force utility user expressed as a weighted sum values for each objective, do not make such...

The problem of identifying the parameters of the constituent local linear models of Takagi–Sugeno fuzzy models is considered. In order to address the tradeoff between global model accuracy and interpretability of the local models as linearizations of a nonlinear system, two multiobjective identification algorithms are studied. Particular attention is paid to the analysis of conflicts between ob...

In this paper a new method based on Utility and Decision theory is presented to deal with structured documents. The aim of the application of these methodologies is to refine a first ranking of structural units, generated by means of an Information Retrieval Model based on Bayesian Networks. Units are newly arranged in the new ranking by combining their posterior probabilities, obtained in the ...

In this work, we propose an hybrid multi-objective optimization design procedure for PI controller tuning. This procedure focuses on reliability-based optimization instances, where Montecarlo methods are used to evaluate quantitatively the performance degradation of a controller, due to unexpected or unmodeled dynamics. The procedure is evaluated on a non-linear Peltier process. The presented r...

nowadays multicriteria decision making (mcdm) methods are a useful tool for investigating natural resources and toaddress problems related to hydro systems. the goal of this research was to assess the daliri standardization method(dsm) to prioritize and make selections for application to mcdm. and to compare the dsm method with the utilityadditive (uta) method. the (dsm) method, unlike the (uta...