308,516 research outputs found

    Adaptation is a Game

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    Control data variants of game models such as Interface Automata are suitable for the design and analysis of self-adaptive systems

    Adaptation is a game

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    Control data variants of game models such as Interface Automata are suitable for the design and analysis of self-adaptive systems

    Stability and Diversity in Collective Adaptation

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    We derive a class of macroscopic differential equations that describe collective adaptation, starting from a discrete-time stochastic microscopic model. The behavior of each agent is a dynamic balance between adaptation that locally achieves the best action and memory loss that leads to randomized behavior. We show that, although individual agents interact with their environment and other agents in a purely self-interested way, macroscopic behavior can be interpreted as game dynamics. Application to several familiar, explicit game interactions shows that the adaptation dynamics exhibits a diversity of collective behaviors. The simplicity of the assumptions underlying the macroscopic equations suggests that these behaviors should be expected broadly in collective adaptation. We also analyze the adaptation dynamics from an information-theoretic viewpoint and discuss self-organization induced by information flux between agents, giving a novel view of collective adaptation.Comment: 22 pages, 23 figures; updated references, corrected typos, changed conten

    The Role of Proactive Adaptation in International Climate Change Mitigation Agreements

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    This paper investigates the role of proactive adaptation in international mitigation coalition formation. Adaptation is introduced into a three stage cartel game of coalition formation. We analytically derive the optimal level of mitigation and proactive adaptation for the singletons and coalition members. We introduce the AD-STACO model which is constructed based on the STACO model, which is an applied three-stage cartel formation model with 12 heterogenous regions

    Oscillatory dynamics in evolutionary games are suppressed by heterogeneous adaptation rates of players

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    Game dynamics in which three or more strategies are cyclically competitive, as represented by the rock-scissors-paper game, have attracted practical and theoretical interests. In evolutionary dynamics, cyclic competition results in oscillatory dynamics of densities of individual strategists. In finite-size populations, it is known that oscillations blow up until all but one strategies are eradicated if without mutation. In the present paper, we formalize replicator dynamics with players that have different adaptation rates. We show analytically and numerically that the heterogeneous adaptation rate suppresses the oscillation amplitude. In social dilemma games with cyclically competing strategies and homogeneous adaptation rates, altruistic strategies are often relatively weak and cannot survive in finite-size populations. In such situations, heterogeneous adaptation rates save coexistence of different strategies and hence promote altruism. When one strategy dominates the others without cyclic competition, fast adaptors earn more than slow adaptors. When not, mixture of fast and slow adaptors stabilizes population dynamics, and slow adaptation does not imply inefficiency for a player.Comment: 4 figure

    Game Theory Models for the Verification of the Collective Behaviour of Autonomous Cars

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    The collective of autonomous cars is expected to generate almost optimal traffic. In this position paper we discuss the multi-agent models and the verification results of the collective behaviour of autonomous cars. We argue that non-cooperative autonomous adaptation cannot guarantee optimal behaviour. The conjecture is that intention aware adaptation with a constraint on simultaneous decision making has the potential to avoid unwanted behaviour. The online routing game model is expected to be the basis to formally prove this conjecture.Comment: In Proceedings FVAV 2017, arXiv:1709.0212
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