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Multi-Round Cooperative Search Games with Multiple Players
[article]
2020
arXiv
pre-print
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Assume that a treasure is placed in one of M boxes according to a known distribution and that k searchers are searching for it in parallel during T rounds. ...
We show that this principle holds for a class of games, which we call monotonously scalable games. This applies in particular to our search game, assuming the sharing policy, in which C(s)=1/s. ...
Unfortunately, however, although many animals engage in search over multiple sites, much less is known about relevant game theoretical aspects is such multi-round settings. ...
arXiv:1811.01270v3
fatcat:ekudy2sc2ffnxpjs4fgwv6bmcq
Multi-Round Cooperative Search Games with Multiple Players
2019
International Colloquium on Automata, Languages and Programming
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For general congestion policies, we show how to polynomially find, for any θ > 0, a symmetric multiplicative Together with an appropriate reward policy, a central entity can suggest players to play a particular ...
Assume that a treasure is placed in one of M boxes according to a known distribution and that k searchers are searching for it in parallel during T rounds. ...
case, whereas they are not in the multi-round game. ...
doi:10.4230/lipics.icalp.2019.146
dblp:conf/icalp/KormanR19
fatcat:5mc3epu63zeqddlvdhkuxds3gy
Adaptive Two-stage Learning Algorithm for Repeated Games
2016
Proceedings of the 8th International Conference on Agents and Artificial Intelligence
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We conducted experiments in which our proposed agents played ten kinds of games in self-play and with other agents. ...
To analyze such interactions, we consider these interactions as a game and people as agents equipped with reinforcement learning algorithms. ...
Consequently, both players are satisfied with a payoff that is not the largest one. S-alg stops searching for other actions and is therefore prone to a shortened search. ...
doi:10.5220/0005711000470055
dblp:conf/icaart/FujitaMFN16
fatcat:d4a4zavutzaklbvsd62za3zqbm
Designing sustainable supply chains
2021
Multiple Criteria Decision Making
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Game theory has become a useful instrument in the analysis of supply chains with multiple agents. ...
Multiple criteria analysis and game theory is a natural choice to effectively analyze and model decision making in such multiple agent situation with multiple criteria where the outcome depends on the ...
The pair (N, v ) is called a cooperative game of n players in the characteristic function form. ...
doi:10.22367/mcdm.2021.16.03
fatcat:obrhu3eq7vespajydijuqgnu2q
An Improved Potential Game Theory Based Method for Multi-UAV Cooperative Search
2020
IEEE Access
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INDEX TERMS Multiple UAVs, cooperative search, potential game, binary log linear learning algorithm. ...
However, there exist some new challenges in the multi-UAV cooperative search, such as collaborative control and search area covering problems. ...
So game theory has caught great attention recently in the multi-UAV cooperative search field. ...
doi:10.1109/access.2020.2978853
fatcat:swkxlhn72rbczod45dbfau5rqe
Optimal Strategies of the Iterated Prisoner's Dilemma Problem for Multiple Conflicting Objectives
2006
2006 IEEE Symposium on Computational Intelligence and Games
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In this paper, we present a new paradigm of searching optimal strategies in the game of Iterated Prisoner's Dilemma using multiple objective evolutionary algorithms. ...
We present the results obtained with this new method, and also the common pattern emerging from the set of non-dominated strategies so obtained. ...
The winner of the game is the player with the maximum payoff at the end of the round robin tournament. ...
doi:10.1109/cig.2006.311701
dblp:conf/cig/MittalD06
fatcat:ebgvw42vbjhu7iuyzuo5hblpdy
Optimal Strategies of the Iterated Prisoner's Dilemma Problem for Multiple Conflicting Objectives
2009
IEEE Transactions on Evolutionary Computation
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In this paper, we present a new paradigm of searching optimal strategies in the game of Iterated Prisoner's Dilemma using multiple objective evolutionary algorithms. ...
We present the results obtained with this new method, and also the common pattern emerging from the set of non-dominated strategies so obtained. ...
The winner of the game is the player with the maximum payoff at the end of the round robin tournament. ...
doi:10.1109/tevc.2008.2009459
fatcat:ojidmszjzrg2tbmfbvxwepofey
Optimizing Bidders Selection of Multi-Round Procurement Problem in Software Project Management Using Parallel Max-Min Ant System Algorithm
2020
Computers Materials & Continua
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bidders of multi-round procurement problem in software project management. ...
To this end, we introduce an approach that proposes: (i) A Game-theoretic model of multiround procurement problem (ii) A Nash equilibrium strategy corresponds to multi-round strategy bid (iii) An application ...
We study infinite games of perfect information played by multiple players, all players of a game pick and join to create a blended procedure, which is a combination of beliefs about probabilities over ...
doi:10.32604/cmc.2020.012464
fatcat:bvrndqdikjelvg2fl72tdu7kwy
Negotiating Team Formation Using Deep Reinforcement Learning
[article]
2020
arXiv
pre-print
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fair solutions predicted by cooperative game theory. ...
Various approaches for multi-agent negotiation have been proposed, but typically only work for particular negotiation protocols. ...
To determine the expected utility of a player i in a game with T rounds, we can examine the acceptance threshold of that player a t=T −1 i . ...
arXiv:2010.10380v1
fatcat:6ztnplwaoncahmloxr6f25orfi
A Novel Particle Swarm Optimization Approach to Support Decision-Making in the Multi-Round of an Auction by Game Theory
2020
International Journal of Computational Intelligence Systems
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To this end, we introduce an approach that proposes (i) a game-theoretic model of the multi-round procurement problem; (ii) a Nash equilibrium strategy corresponding to the multi-round strategy bid; and ...
In this paper, game-theoretic optimization by particle swarm optimization (PSO) is used to determine the Nash equilibrium value, in order to resolve the confusion in choosing appropriate bidders in multi-round ...
We study infinite games of perfect information played by multiple players, all players of a game pick and join to create a blended procedure, which is a combination of beliefs about probabilities over ...
doi:10.2991/ijcis.d.200828.002
fatcat:pldkqo3rp5ganodkn74xauj4um
A Generic Agent Architecture for Cooperative Multi-agent Games
2017
Proceedings of the 9th International Conference on Agents and Artificial Intelligence
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The goal of this dissertation is to propose a high level generic architecture for the development of agents able to effectively play games with strong social components and a mix of competition and cooperation ...
are difficult to apply to this category of games, due to the often enormous search trees and the difficulty in calculating the value of a player's position or move. ...
In the field of game theory, a game is considered a cooperative game if players are able to form binding commitments with each-other. ...
doi:10.5220/0006253101070118
dblp:conf/icaart/MarinheiroC17
fatcat:sqzc2xounrefhkojj3g2ptznxy
Formal Methods for An Iterated Volunteer's Dilemma
[article]
2021
arXiv
pre-print
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In this work, we design a model framework and explore The Volunteer's Dilemma with the goals of 1) modeling it as a stochastic concurrent multiplayer game, 2) constructing properties to verify model correctness ...
with expected local and global rewards over a finite time horizon. ...
Our model was presented as a concurrent stochastic game in which players were guided to cooperate with one another. ...
arXiv:2008.12846v3
fatcat:bchlpbcxqbbzlmng6aaiqm5irm
Core-Periphery Segregation in Evolving Prisoner's Dilemma Networks
[article]
2012
arXiv
pre-print
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Our large group prisoner's dilemma experiments with exit and partner choice options show that core-periphery segregation of cooperators and defectors drives the emergence of cooperation. ...
Cooperators' Quit-for-Tat and defectors' Roving strategy lead to a highly asymmetric core and periphery structure. ...
In this case, a player would limit the search and be satisfied with a few links with suboptimal game outcomes. ...
arXiv:1105.0515v2
fatcat:eweuwmvu3bejlailg4j2gbcygi
An Overview of Cooperative and Competitive Multiagent Learning
[chapter]
2006
Lecture Notes in Computer Science
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Multi-agent systems (MASs) is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexities arising from their interactions ...
In this survey we give an overview of multi-agent learning research in a spectrum of areas, including reinforcement learning, evolutionary computation, game theory, complex systems, agent modeling, and ...
This is encoded in the Tit-for-Tat strategy that initially starts the game by cooperating. A defection by the opponent is punished by a defection in the next round of play. ...
doi:10.1007/11691839_1
fatcat:wszsoftrobh67lq7ypjrqs3wxa
AI in Games: Techniques, Challenges and Opportunities
[article]
2021
arXiv
pre-print
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Various game AI systems (AIs) have been developed such as Libratus, OpenAI Five and AlphaStar, beating professional human players. ...
With breakthrough of AlphaGo, AI in human-computer game has become a very hot topic attracting researchers all around the world, which usually serves as an effective standard for testing artificial intelligence ...
Multi-agent cooperation. Most board games and card games are purely competitive, where no cooperation between players is required. ...
arXiv:2111.07631v1
fatcat:g4sbl6v73rg4jdijj4qfi3eusq
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