Deciphering chaos in evolutionary games.

Chaos

Department of Physics, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh 208016, India.

Published: December 2020


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

A discrete-time replicator map is a prototype of evolutionary selection game dynamical models that have been very successful across disciplines in rendering insights into the attainment of the equilibrium outcomes, like the Nash equilibrium and the evolutionarily stable strategy. By construction, only the fixed-point solutions of the dynamics can possibly be interpreted as the aforementioned game-theoretic solution concepts. Although more complex outcomes like chaos are omnipresent in nature, it is not known to which game-theoretic solutions they correspond. Here, we construct a game-theoretic solution that is realized as the chaotic outcomes in the selection monotone game dynamic. To this end, we invoke the idea that in a population game having two-player-two-strategy one-shot interactions, it is the product of the fitness and the heterogeneity (the probability of finding two individuals playing different strategies in the infinitely large population) that is optimized over the generations of the evolutionary process.

Download full-text PDF

Source
http://dx.doi.org/10.1063/5.0029480DOI Listing

Publication Analysis

Top Keywords

game-theoretic solution
8
deciphering chaos
4
chaos evolutionary
4
evolutionary games
4
games discrete-time
4
discrete-time replicator
4
replicator map
4
map prototype
4
prototype evolutionary
4
evolutionary selection
4

Similar Publications

Adaptive dynamics describes a deterministic approximation of the evolution of scalar- and function-valued traits. We construct an evolutionary process for a game-theoretic model which may describe the evolution of microbes. In our analysis, we demonstrate the existence of solutions to the adaptive dynamics and determined their regularity.

View Article and Find Full Text PDF

Introduction: Ovarian Cancer (OC) is one of the leading causes of cancer deaths among women. Despite recent advances in the medical field, such as surgery, chemotherapy, and radiotherapy interventions, there are only marginal improvements in the diagnosis of OC using clinical parameters, as the symptoms are very non-specific at the early stage. Owing to advances in computational algorithms, such as ensemble machine learning, it is now possible to identify complex patterns in clinical parameters.

View Article and Find Full Text PDF

In this paper, we focus on developing self-organizing algorithms aimed at solving, in a distributed way, the coverage problem in Wireless Sensor Networks (WSNs). For this purpose, we apply a game-theoretical framework based on an application of a variant of the Spatial Prisoner's Dilemma game. The framework is used to build a multi-agent system, where agent-players in the process of iterated games tend to achieve a Nash equilibrium, providing them the possible maximal values of payoffs.

View Article and Find Full Text PDF

A Game Model and Fault Recovery Algorithm for SDN Multi-Domain.

Sensors (Basel)

December 2024

The College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Software-defined networking (SDN) offers an effective solution for flexible management of Wireless Sensor Networks (WSNs) by separating control logic from sensor nodes. This paper tackles the challenge of timely recovery from SDN controller failures and proposes a game theoretic model for multi-domain controllers. A game-enhanced autonomous fault recovery algorithm for SDN controllers is proposed, which boasts fast fault recovery and low migration costs.

View Article and Find Full Text PDF

The framework of mean-field games (MFGs) is used for modeling the collective dynamics of large populations of non-cooperative decision-making agents. We formulate and analyze a kinetic MFG model for an interacting system of non-cooperative motile agents with inertial dynamics and finite-range interactions, where each agent is minimizing a biologically inspired cost function. By analyzing the associated coupled forward-backward in a time system of nonlinear Fokker-Planck and Hamilton-Jacobi-Bellman equations, we obtain conditions for closed-loop linear stability of the spatially homogeneous MFG equilibrium that corresponds to an ordered state with non-zero mean speed.

View Article and Find Full Text PDF