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Displaying similar documents to “Cooperative networks games with elastic demands”

Modeling shortest path games with Petri nets: a Lyapunov based theory

Julio Clempner (2006)

International Journal of Applied Mathematics and Computer Science

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In this paper we introduce a new modeling paradigm for shortest path games representation with Petri nets. Whereas previous works have restricted attention to tracking the net using Bellman's equation as a utility function, this work uses a Lyapunov-like function. In this sense, we change the traditional cost function by a trajectory-tracking function which is also an optimal cost-to-target function. This makes a significant difference in the conceptualization of the problem domain,...

The Give and Take game: Analysis of a resource sharing game

Pedro Mariano, Luís Correia (2015)

International Journal of Applied Mathematics and Computer Science

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We analyse Give and Take, a multi-stage resource sharing game to be played between two players. The payoff is dependent on the possession of an indivisible and durable resource, and in each stage players may either do nothing or, depending on their roles, give the resource or take it. Despite these simple rules, we show that this game has interesting complex dynamics. Unique to Give and Take is the existence of multiple Pareto optimal profiles that can also be Nash equilibria, and a...

Blocking Wythoff Nim.

Larsson, Urban (2011)

The Electronic Journal of Combinatorics [electronic only]

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Convexity of production, common pool and oligopoly games: a survey

Theo S. H. Driessen, Holger Meinhardt (2006)

Banach Center Publications

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The paper surveys a uniform proof technique of the convexity property for three different cooperative TU games arising from three different economical settings. The production economy, common pool situation and oligopoly framework involve a cost function, but different production functions. Each of the three corresponding game theoretic models refers to some maximization problem described by optimizing a certain net profit function over all feasible production levels. The current mathematical...

Risk-sensitive Markov stopping games with an absorbing state

Jaicer López-Rivero, Rolando Cavazos-Cadena, Hugo Cruz-Suárez (2022)

Kybernetika

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This work is concerned with discrete-time Markov stopping games with two players. At each decision time player II can stop the game paying a terminal reward to player I, or can let the system to continue its evolution. In this latter case player I applies an action affecting the transitions and entitling him to receive a running reward from player II. It is supposed that player I has a no-null and constant risk-sensitivity coefficient, and that player II tries to minimize the utility...

Modern approaches to modeling user requirements on resource and task allocation in hierarchical computational grids

Joanna Kołodziej, Fatos Xhafa (2011)

International Journal of Applied Mathematics and Computer Science

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Tasks scheduling and resource allocation are among crucial issues in any large scale distributed system, including Computational Grids (CGs). These issues are commonly investigated using traditional computational models and resolution methods that yield near-optimal scheduling strategies. One drawback of such approaches is that they cannot effectively tackle the complex nature of CGs. On the one hand, such systems account for many administrative domains with their own access policies,...

Evolving small-board Go players using coevolutionary temporal difference learning with archives

Krzysztof Krawiec, Wojciech Jaśkowski, Marcin Szubert (2011)

International Journal of Applied Mathematics and Computer Science

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We apply Coevolutionary Temporal Difference Learning (CTDL) to learn small-board Go strategies represented as weighted piece counters. CTDL is a randomized learning technique which interweaves two search processes that operate in the intra-game and inter-game mode. Intra-game learning is driven by gradient-descent Temporal Difference Learning (TDL), a reinforcement learning method that updates the board evaluation function according to differences observed between its values for consecutively...