Learning is inherently connected with Interactive Multiobjective Optimization (IMO), therefore, a systematic analysis of IMO from the learning perspective is worthwhile. After an introduction to the nature and the interest of learning within IMO, we consider two complementary aspects of learning: individual learning, i.e., what the decision maker can learn, and model or machine learning, i.e., ...

Decision makers are faced with an ever-growing collection of information, and an ever-growing level of complexity with respect to the types of decisions being made. Appropriately designed computerized decision support tools are needed to support the decision maker in the various tasks that they must undertake in evaluating the information, arriving at a decision, and solving the problem. Howeve...

In adversarial situations, the input data to an algorithm could be manipulated to make the algorithm produce erroneous output or to make a wrong decision. The paper presents a formal definition and a model of algorithm manipulation from a game-theoretic point of view. Algorithm manipulation is viewed as a game between a decision maker and an adversary. The decision maker runs an algorithm to ma...

In the present work we deal with the concept of alpha-fair resource allocation in the situation where the decision maker (in our case, the base station) does not have complete information about environment. Namely, we develop a concept of α-fairness under uncertainty to allocate power resource in the presence of a jammer under two types of uncertainty: (a) the decision maker does not have compl...

We propose a simple model for an atomic switch-based decision maker (ASDM), and show that, as long as its total volume of precipitated Ag atoms is conserved when coupled with suitable operations, an atomic switch system provides a sophisticated “decision-making” capability that is known to be one of the most important intellectual abilities in human beings. We considered the multi-armed bandit ...

This study explores the decision outcomes achieved by 122 subjects using a DSS for an insolvency decision making task. Decision quality improvements occur as a result of collaboration between the decision maker and the DSS at two crucial points in the decision making process. Firstly when the decision maker initially interacts with the DSS to generate a recommendation, and secondly when the dec...

This paper presents a rational theory of categorization and similarity-based reasoning. I study a model of sequential learning in which the decision maker infers unknown properties of an object from information about other objects. The decision maker may use the following heuristics: divide objects into categories with similar properties and predict that a member of a category has a property if...

We consider an adversarial online learning setting where a decision maker can choose an action in every stage of the game. In addition to observing the reward of the chosen action, the decision maker gets side observations on the reward he would have obtained had he chosen some of the other actions. The observation structure is encoded as a graph, where node i is linked to node j if sampling i ...

This paper considers multiobjective integer programming problems involving random variables in constraints. Using the concept of simple recourse, the formulated multiobjective stochastic simple recourse problems are transformed into deterministic ones. For solving transformed deterministic problems efficiently, we also introduce genetic algorithms with double strings for nonlinear integer progr...

With vast improvements in healthcare in recent decades, people are living longer but often with higher rates of morbidity and chronic illnesses. This has resulted in a higher proportion of the population who may benefit from early end-of-life 'conversation and planning', but also gives healthcare professionals more time during which these discussions are relevant, as people live longer with the...