Game Theory

Petrosyan, Leon A.; Zenkevich, Nikolay A.

doi:10.1142/9824

Cited by 30 publications

(27 citation statements)

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“…In cooperative setting players seek a set of strategies that yields a Pareto optimal solution, hence they maximize the sum of their individual payoffs. To determine the share of each player from the total payoff, that is called the imputation, some solution concepts, such as NM-solution, the core and the Shapley value are applied; see [25][26][27]. To construct the imputation of the cooperative game the characteristic function reflecting the payoff of any coalition of the players should be determined.…”

Section: Dynamic Stability Of Cooperative Solutionmentioning

confidence: 99%

Rational Behavior in Dynamic Multicriteria Games

Rettieva

2020

Mathematics

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We consider a dynamic, discrete-time, game model where n players use a common resource and have different criteria to optimize. To construct a multicriteria Nash equilibrium the bargaining solution is adopted. To design a multicriteria cooperative equilibrium, a modified bargaining scheme that guarantees the fulfillment of rationality conditions is applied. The concept of dynamic stability is adopted for dynamic multicriteria games. To stabilize the multicriteria cooperative solution a time-consistent payoff distribution procedure is constructed. The conditions for rational behavior, namely irrational-behavior-proofness condition and each step rational behavior condition are defined for dynamic multicriteria games. To illustrate the presented approaches, a dynamic bi-criteria bioresource management problem with many players is investigated.

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Section: Dynamic Stability Of Cooperative Solutionmentioning

confidence: 99%

Rational Behavior in Dynamic Multicriteria Games

Rettieva

2020

Mathematics

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“…Sensible pragmatism tells them to go the shortest way to solving the problem, but "I am the creator" requires the realization of potential, the development of creative capabilities, the realization of the team interaction possibilities. In this case, let us recall the provisions of a "game theory" ("Nash equilibrium") about optimal behavioral strategies (Petrosyan et al, 2012). Students, as a rule, choose the best way: they use network resources and at the same time give free rein to creative abilities.…”

Section: Fig 2 Model Of Group Project Activities Of Students In Thementioning

confidence: 99%

Design of Students’ Creative Activity in the Conditions of «Digital Freedom»: Comparative Analysis of Group and Individual Strategies

Andreeva¹,

Sibgatullina²,

Ratner³

2020

ARPHA Proceedings

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The modern neural network, as a prototype of artificial intelligence, becomes not just an assistant in student learning, but its co-author, co-creator, a partner and a mentor. The ever-increasing and less-controlled capabilities of artificial intelligence in the field of collecting and analyzing information, organizing experiments, modeling and forecasting, generating original content, call into question the very principle of freedom of human creativity. The concept of "digital freedom" is introduced in the article to describe the new conditions of students' creative activity. The information environment is considered as a resource and, at the same time, a barrier for traditional approaches, which are adopted in pedagogy, to project creative activities of students. In the situation of digital freedom, new effective models and strategies for organizing, conducting and evaluating student projects arise. The article provides a review and comparative analysis of group and individual design strategies, introduces and describes new strategies for project activities based on collective leadership and co-creation with artificial intelligence. The experiences of project creative work performed by bachelor's students and master's students of the Higher School of Journalism of the Institute of Social and Philosophical Sciences and Mass Communications, the Institute of International Relations and the Institute of Psychology and Education of KFU were analyzed.

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“…when there are two equivalent alternatives, the i th player will choose the option which is more advantages for other player [9]. In our case each player moves their own mobile agents so that it does not increase the sub graph diameter of another player.…”

Section: Alternatives and The Pay-off Functionmentioning

confidence: 99%

The strategic placement of mobile agents on a hexagonal graph using game theory

Plekhanova

Gromova

Gromov

et al. 2017

2017 XXVI International Conference on Information, Communication and Automation Technologies (ICAT)

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Abstract-This paper considers an application of Dynamic Game Theory with the goal of increasing the performance of a Mobile Ad Hoc Network in relation to increasing packet delivery ratio and reducing end-to-end delay by the strategic placement of drones. A multi-stage sequential game of two players, each with one drone is played out in a scenario depicted by a hexagonal graph, obstacles such as forests are also included. The algorithm for the game has been implemented in JavaScript and the results show that the best strategic locations of the placement of the drones can be established during the sequential moves of the players. Results also show that the Nash Equilibrium is achieved during play.

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Game Theory

Cited by 30 publications

References 0 publications

Rational Behavior in Dynamic Multicriteria Games

Rational Behavior in Dynamic Multicriteria Games

Design of Students’ Creative Activity in the Conditions of «Digital Freedom»: Comparative Analysis of Group and Individual Strategies

The strategic placement of mobile agents on a hexagonal graph using game theory

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