Evolutionary Coalitional Games

Płatkowski, Tadeusz

doi:10.1007/s13235-015-0145-3

Cited by 12 publications

(8 citation statements)

References 21 publications

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“…In particular, we have shown that the structure of the Nash equilibria for the Hawk-Dove and Leader games is identical to that of (Anti-)Coordination Game (see Methods, Proposition 8), which suggests that the transparency has a strong effect on successful strategies in these games as well. As a future work, it would also be interesting to extend the transparent game framework to N-agent interactions [60][61][62], to provide an account of naturalistic dynamics in groups.…”

Section: Discussionmentioning

confidence: 99%

Emergence and suppression of cooperation by action visibility in transparent games

et al. 2020

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Real-world agents, humans as well as animals, observe each other during interactions and choose their own actions taking the partners' ongoing behaviour into account. Yet, classical game theory assumes that players act either strictly sequentially or strictly simultaneously without knowing each other's current choices. To account for action visibility and provide a more realistic model of interactions under time constraints, we introduce a new gametheoretic setting called transparent games, where each player has a certain probability of observing the partner's choice before deciding on its own action. By means of evolutionary simulations, we demonstrate that even a small probability of seeing the partner's choice before one's own decision substantially changes the evolutionary successful strategies. Action visibility enhances cooperation in an iterated coordination game, but reduces cooperation in a more competitive iterated Prisoner's Dilemma. In both games, "Win-stay, loseshift" and "Tit-for-tat" strategies are predominant for moderate transparency, while a "Leader-Follower" strategy emerges for high transparency. Our results have implications for studies of human and animal social behaviour, especially for the analysis of dyadic and group interactions.

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Section: Discussionmentioning

confidence: 99%

Emergence and suppression of cooperation by action visibility in transparent games

et al. 2020

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“…It may also be of interest to study structural changes in the social dilemmas, which may result in transforming the dilemmas, cf. e.g., [17]. One could also study in this respect the role of the price of anarchy, the price of stability and other characteristics of the social dilemmas, cf.…”

Section: Discussionmentioning

confidence: 99%

“…We could call such a game the 1 2 -th order A-R dilemma, due to the following arguments: Increasing P D (2) in this game from 3, e.g., to 4, we obtain the zeroth-order A-R dilemma, whereas decreasing P D (2) from 3, e.g., to 2 1 2 , we obtain the first-order A-R game, with two polymorphic equilibria: unstable 2 7 and stable 6 7 . Similarly we could introduce higher-order "fractional" dilemmas, e.g., 1 [17,15,10,9,3,18,13,12,10,2] is a second-order R-R game, with two stable (and one unstable) polymorphic equilibria. The game [20,16,13,11,0,19,18,16,7,3] is a first-order five-person A-A game, with one stable (and two unstable) polymorphic equilibria.…”

Section: Lemma 4 the N-person Social Dilemma IV Is The First-order R-mentioning

confidence: 99%

On Derivation and Evolutionary Classification of Social Dilemma Games

Płatkowski

2015

Dyn Games Appl

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We propose an axiomatic derivation and a classification of multiperson social dilemma games. For the two-person symmetric games, the axiomatization leads to three types of the social dilemmas only: the Prisoner's Dilemma (PD) game, the Chicken (Snowdrift) game and the Stag Hunt game. The popular multiperson games, such as for example the N-person PD, the Public Goods, the Tragedy of the Commons, the Volunteer's Dilemma and the Assurance game, are included in the proposed frame. For general social dilemma games with arbitrary payoffs, their simple classification is proposed, based on the number of stable equilibria of the corresponding replicator dynamics.

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“…To perform such modeling, prior to formulating the game, we first use stochastic geometry tools [30], [31] to characterize metrics, such as the distribution of distances between MTDs and inter-cluster interference. Then, based on these system parameters, In this section, we propose an evolutionary game [27]- [29], [32]- [35] for clustering an infinite number of MTDs, in order to reduce transmission power for each MTD as well as the number of redundant bits sent to the BS. This approach is fully distributed, as it allows an infinite number of MTDs to self-organize into clusters based on increasing data correlation and reducing transmission power.…”

Section: A Problem Formulationmentioning

confidence: 99%

Evolutionary Games for Correlation-Aware Clustering in Massive Machine-to-Machine Networks

Sawyer

Soorki

Saad

et al. 2019

IEEE Trans. Commun.

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In this paper, the problem of self-organizing, correlation-aware clustering is studied for a dense network of machine-type devices (MTDs) deployed over a cellular network. In dense machine-tomachine networks, MTDs are typically located within close proximity and will gather correlated data, and, thus, clustering MTDs based on data correlation will lead to a decrease in the number of redundant bits transmitted to the base station. To analyze this clustering problem, a novel utility function that captures the average MTD transmission power per cluster is derived, as a function of the MTD location, cluster size, and inter-cluster interference. Then, the clustering problem is formulated as an evolutionary game, which models the interactions among the massive number of MTDs, in order to decrease MTD transmission power. To solve this game, a distributed algorithm is proposed to allow the infinite number of MTDs to autonomously form clusters. It is shown that the proposed distributed algorithm converges to an evolutionary stable strategy (ESS), that is robust to a small portion of MTDs deviating from the stable cluster formation at convergence. The maximum fraction of MTDs that can deviate from the ESS, while still maintaining a stable cluster formation is derived. Simulation results show that the proposed approach can effectively cluster MTDs with highly correlated data, which, in turn, enables those MTDs to eliminate a large number of redundant bits. The results show that, on average, using the proposed approach yields reductions of up to 23.4% and 9.6% in terms of the transmit power per cluster, compared to forming clusters with the maximum possible size and uniformly selecting a cluster size, respectively. A preliminary version of this work appeared in IEEE GLOBECOM 2017 [1]. 2 I. INTRODUCTION Machine-to-machine (M2M) communications is an important component of the emerging Internet of Things (IoT) system, as it enables advanced networked applications such as smart home technologies, smart grid, healthcare, drone systems, manufacturing systems, and surveillance [2]-[7]. Within an M2M network, a massive number of machine-type devices (MTDs) will be densely deployed over wireless cellular networks [8]. An MTD can be a sensor, actuator, or smart meter whose typical role is to sense or measure an environment, and transmit the collected data to cellular base stations (BSs). MTDs enable real-time monitoring and control of any physical environment, without direct human involvement, thus making processes more efficient and improving human welfare [4], [9]. Since the number of MTDs is expected to be massive and much larger than the number of cellular-type devices (CTDs), it is expected that a massive-scale MTD deployment will lead to quality-of-service (QoS) degradation, increased traffic and signaling, increased latency, and reduced reliability [4]. Therefore, deploying MTDs over cellular networks faces many challenges ranging from network modeling to resource management, massive-scale, access, and MTD clustering as mention...

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Evolutionary Coalitional Games

Cited by 12 publications

References 21 publications

Emergence and suppression of cooperation by action visibility in transparent games

Emergence and suppression of cooperation by action visibility in transparent games

On Derivation and Evolutionary Classification of Social Dilemma Games

Evolutionary Games for Correlation-Aware Clustering in Massive Machine-to-Machine Networks

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