Maciej Swiechowski

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The term General Game Playing (GGP) refers to a subfield of Artificial Intelligence which aims at developing agents able to effectively play many games from a particular class (finite, deterministic). It is also the name of the annual competition proposed by Stanford Logic Group at Stanford University, which provides a framework for testing and evaluating(More)
The goal of General Game Playing (GGP) has been to develop computer programs that can perform well across various game types. It is natural for human game players to transfer knowledge from games they already know how to play to other similar games. GGP research attempts to design systems that work well across different game types, including unknown new(More)
—Capacitated Vehicle Routing Problem (CVRP) is a well-known NP-hard optimization problem. In this paper, we transform it into a non-deterministic dynamic version by introducing traffic jams (TJ). The paper is the first attempt of applying the Upper Confidence Bounds applied to Trees (UCT) algorithm in the domain of dynamic transportation problems. In short,(More)
—The paper concerns the problem of reaching consensus among agents in group decision making. A popular framework of individual preferences expressed as (fuzzy) preference relations is adopted. The consensus reaching process is assumed to be based on a discussion in the group of agents, which is expected to make the initially expressed preferences closer one(More)