Bio-Inspired Evolutionary Game Dynamics in Symmetric and Asymmetric Models

Stella, Leonardo; Bauso, Dario

doi:10.1109/lcsys.2018.2838445

Cited by 12 publications

(17 citation statements)

References 18 publications

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“…Before we can present the macroscopic dynamics for the problem originating in the context of emergency evacuations, we introduce the following definition of expected gain given x for our game dynamics. This constitutes the first contribution of the paper, and takes inspiration from the model developed in the context of swarm behavior, see [12]. Definition 1: (Expected gain) Let A be a payoff matrix.…”

Section: Evolutionary Game Dynamicsmentioning

confidence: 99%

Evolutionary Game Dynamics for Crowd Behavior in Emergency Evacuations

Mason

Stella

Bauso

2020

2020 59th IEEE Conference on Decision and Control (CDC)

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Section: Evolutionary Game Dynamicsmentioning

confidence: 99%

Evolutionary Game Dynamics for Crowd Behavior in Emergency Evacuations

Mason

Stella

Bauso

2020

2020 59th IEEE Conference on Decision and Control (CDC)

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“…In the existing literature, often the dynamics of a single group of individuals is studied, [1], [3], [9]. Here, the evolutionary dynamics are inspired on a biological model on swarms of bees, see e.g.…”

Section: B Related Workmentioning

confidence: 99%

“…In this paper we study networked bio-inspired models, where a group of individuals has the objective of reaching consensus on one of the available options. In recent years there has already been a surge in amount of published literature on this topic, see for example [1], [3], [8] and [9]. Usually, a group of individuals is considered and every player of the group can choose between two options, 1 or 2, or can choose to be uncommitted.…”

Section: Introductionmentioning

confidence: 99%

Networked Bio-Inspired Evolutionary Dynamics on a Multi-Population

Baar

Bauso

2019

2019 18th European Control Conference (ECC)

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We consider a multi-population, represented by a network of groups of individuals. Every player of each group can choose between two options, and we study the problem of reaching consensus. The dynamics not only depend on the dynamics within the group, but they also depend on the topology of the network, so neighboring groups influence individuals as well. First, we develop a mathematical model of this networked bio-inspired evolutionary behavior and we study its steadystate. We look at the special case where the underlying network topology is a regular and unweighted graph and show that the steady-state is a consensus equilibrium. A sufficient condition for exponential stability is given. Finally, a related networked dynamical system with connections to the Bass model is studied and we conclude the paper with simulations.

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“…A range of mathematical models have been extensively investigated, among which the replicator dynamics model is the most wellknown [10]. Powerful theories and tools originating from evolutionary game theory facilitate the study of complex system behaviors of biological, ecological, social, and engineering fields [19], [12], [14], [22], [30]. In the classic game setting, the payoffs in each two-player game are usually predetermined in the form of constant payoff matrices.…”

Section: Introductionmentioning

confidence: 99%

Limit Cycles Analysis and Control of Evolutionary Game Dynamics with Environmental Feedback

Gong¹,

Yao²,

Gao³

et al. 2022

Preprint

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Recently, an evolutionary game dynamics model taking into account the environmental feedback has been proposed to describe the co-evolution of strategic actions of a population of individuals and the state of the surrounding environment; correspondingly a range of interesting dynamic behaviors have been reported. In this paper, we provide new theoretical insight into such behaviors and discuss control options. Instead of the standard replicator dynamics, we use a more realistic and comprehensive model of replicator-mutator dynamics, to describe the strategic evolution of the population. After integrating the environment feedback, we study the effect of mutations on the resulting closed-loop system dynamics. We prove the conditions for two types of bifurcations, Hopf bifurcation and Heteroclinic bifurcation, both of which result in stable limit cycles. These limit cycles have not been identified in existing works, and we further prove that such limit cycles are in fact persistent in a large parameter space and are almost globally stable. In the end, an intuitive control policy based on incentives is applied, and the effectiveness of this control policy is examined by analysis and simulations.

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Bio-Inspired Evolutionary Game Dynamics in Symmetric and Asymmetric Models

Cited by 12 publications

References 18 publications

Evolutionary Game Dynamics for Crowd Behavior in Emergency Evacuations

Evolutionary Game Dynamics for Crowd Behavior in Emergency Evacuations

Networked Bio-Inspired Evolutionary Dynamics on a Multi-Population

Limit Cycles Analysis and Control of Evolutionary Game Dynamics with Environmental Feedback

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