Dimitrios Antos

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We present a novel methodology for decisionmaking by computer agents that leverages a computational concept of emotions. It is believed that emotions help living organisms perform well in complex environments. Can we use them to improve the decision-making performance of computer agents? We explore this possibility by formulating emotions as mathematical(More)
Research in the behavioral sciences suggests that emotion can serve important social functions and that, more than a simple manifestation of internal experience, emotion displays communicate one’s beliefs, desires and intentions. In a recent study we have shown that, when engaged in the iterated prisoner’s dilemma with agents that display emotion, people(More)
When interacting with computer agents, people make inferences about various characteristics of these agents, such as their reliability and trustworthiness. These perceptions are significant, as they influence people’s behavior towards the agents, and may foster or inhibit repeated interactions between them. In this paper we investigate whether computer(More)
The effectiveness of a hybrid of simulated annealing (SA) and the simplex algorithm for optimization of a chromatographic separation has been examined. The method has been used to solve optimization problems for separations in batch and continuous chromatographic systems under isocratic and gradient conditions. To verify the robustness of the algorithm a(More)
We present an algorithm that identifies the reasoning patterns of agents in a game, by iteratively examining the graph structure of its Multi-Agent Influence Diagram (MAID) representation. If the decision of an agent participates in no reasoning patterns, then we can effectively ignore that decision for the purpose of calculating a Nash equilibrium for the(More)
The paper presents a computational model for decision-making in a social dilemma that takes into account the other party’s emotion displays. The model is based on data collected in a series of recent studies where participants play the iterated prisoner’s dilemma with agents that, even though following the same action strategy, show different emotion(More)
In complex strategic situations decision-making agents interact with many other agents and have access to many pieces of information throughout their play. This usually leads to game solving being a very complex, almost intractable procedure. Moreover, algorithms for solving games usually fail to explain how the various equilibria come about and how(More)
Bayesian games have been traditionally employed to describe and analyze situations in which players have private information or are uncertain about the game being played. However, computing Bayes-Nash equilibria can be costly, and becomes even more so if the common prior assumption (CPA) has to be abandoned, which is sometimes necessary for a faithful(More)