scholarly journals Two conceptions of evolutionary games: reductive vs effective

2017 ◽  
Author(s):  
Artem Kaznatcheev
Keyword(s):  
Game Theory ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Theoretical Work ◽  
Structured Populations ◽  
Agent Based ◽  
Specific Interpretation ◽  
The Difference ◽  
Games Theory ◽  
Future Work

Evolutionary game theory (EGT) was born from economic game theory through a series of analogies. Given this heuristic genealogy, a number of central objects of the theory (like strategies, players, and games) have not been carefully defined or interpreted. A specific interpretation of these terms becomes important as EGT sees more applications to understanding experiments in microscopic systems typical of oncology and microbiology. In this essay, I provide two interpretations of the central objects of games theory: one that leads to reductive games and the other to effective games. These interpretation are based on the difference between views of fitness as a property of individuals versus fitness as a summary statistic of (sub)populations. Reductive games are typical of theoretical work like agent-based models. But effective games usually correspond more closely to experimental work. However, confusing reductive games for effective games or vice-versa can lead to divergent results, especially in spatially structured populations. As such, I propose that we treat this distinction carefully in future work at the interface of EGT and experiment.

Insights into the Impact of Social Networks on Evolutionary Games

2008 ◽  
pp. 306-323
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Weibull, 1995; Taylor & Jonker, 1978; Nowak & May, 1993) to model the dynamics of adaptive opponent strategies for large population of players. In particular, we explore effects of information propagation through social networks in Evolutionary Games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2010 ◽  
pp. 150-159
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

The chapter explores the use of evolutionary game theory (EGT) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, it explores effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. The chapter presents experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2009 ◽  
pp. 1477-1488
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, we explore effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2009 ◽  
pp. 317-331
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of pl ion propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

scholarly journals USING EVOLUTIONARY GAMES THEORY FOR PLAYERS BEHAVIOR ANALYSIS IN COMPETITIVE SHOOTING GAMES: A LITERATURE REVIEW

2021 ◽  
pp. 101-103
Author(s):  
Luka Baryshych ◽  
Igor Baklan
Keyword(s):  
Game Theory ◽  
Behavior Analysis ◽  
Evolutionary Biology ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Fuzzy Algorithms ◽  
Evolutionary Games Theory ◽  
Games Theory ◽  
Competitive Shooting

The paper is dedicated to the overview of current state of the evolutionary games approach to the building of environments to analyze players behavior. The evolutionary game theory applications differ from the orthodox game theory. Initially, it was used to address problems in evolutionary biology and later was suited for broader range of problems.We will oversee the development of the evolutionary games theory in finance and its applications in behavior analysis in competitive gaming. The paper is focused on replicator dynamics, learning model based on it and its possible application to behavior analysis based on fuzzy algorithms and approaches used in economics to be applied to the new emerging field of cybersports.

scholarly journals Dynamic utility: the sixth reciprocity mechanism for the evolution of cooperation

2020 ◽  
Vol 7 (8) ◽  
pp. 200891 ◽  
Author(s):  
Hiromu Ito ◽  
Jun Tanimoto
Keyword(s):  
Game Theory ◽  
Dynamic Game ◽  
Evolutionary Games ◽  
Evolution Of Cooperation ◽  
Current Status ◽  
Cooperative Behaviour ◽  
Evolutionary Mechanism ◽  
Static Game ◽  
Chicken Game ◽  
The Difference

Game theory has been extensively applied to elucidate the evolutionary mechanism of cooperative behaviour. Dilemmas in game theory are important elements that disturb the promotion of cooperation. An important question is how to escape from dilemmas. Recently, a dynamic utility function (DUF) that considers an individual's current status (wealth) and that can be applied to game theory was developed. The DUF is different from the famous five reciprocity mechanisms called Nowak's five rules. Under the DUF, cooperation is promoted by poor players in the chicken game, with no changes in the prisoner's dilemma and stag-hunt games. In this paper, by comparing the strengths of the two dilemmas, we show that the DUF is a novel reciprocity mechanism (sixth rule) that differs from Nowak's five rules. We also show the difference in dilemma relaxation between dynamic game theory and (traditional) static game theory when the DUF and one of the five rules are combined. Our results indicate that poor players unequivocally promote cooperation in any dynamic game. Unlike conventional rules that have to be brought into game settings, this sixth rule is universally (canonical form) applicable to any game because all repeated/evolutionary games are dynamic in principle.

scholarly journals Aspiration dynamics of multi-player games in finite populations

2014 ◽  
Vol 11 (94) ◽  
pp. 20140077 ◽  
Author(s):  
Jinming Du ◽  
Bin Wu ◽  
Philipp M. Altrock ◽  
Long Wang
Keyword(s):  
Evolutionary Game ◽  
Pairwise Comparison ◽  
Evolutionary Games ◽  
Structured Populations ◽  
Weak Selection ◽  
Additional Information ◽  
Average Abundance ◽  
Imperfect Rationality ◽  
Update Rules ◽  
Limiting Case

On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics.

scholarly journals Dynamical patterns of coexisting strategies in a hybrid discrete-continuum spatial evolutionary game model

2016 ◽  
Author(s):  
A.E.F. Burgess ◽  
P.G. Schofield ◽  
S.F. Hubbard ◽  
M.A.J. Chaplain ◽  
T. Lorenzi
Keyword(s):  
Diffusion Equation ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Reaction Diffusion ◽  
Social Contexts ◽  
Random Motion ◽  
Structured Populations ◽  
Reaction Diffusion Equation ◽  
Modelling Framework ◽  
Dynamical Patterns

AbstractWe present a novel hybrid modelling framework that takes into account two aspects which have been largely neglected in previous models of spatial evolutionary games: random motion and chemotaxis. A stochastic individual-based model is used to describe the player dynamics, whereas the evolution of the chemoattractant is governed by a reaction-diffusion equation. The two models are coupled by deriving individual movement rules via the discretisation of a taxis-diffusion equation which describes the evolution of the local number of players. In this framework, individuals occupying the same position can engage in a two-player game, and are awarded a payoff, in terms of reproductive fitness, according to their strategy. As an example, we let individuals play the Hawk-Dove game. Numerical simulations illustrate how random motion and chemotactic response can bring about self-generated dynamical patterns that create favourable conditions for the coexistence of hawks and doves in situations in which the two strategies cannot coexist otherwise. In this sense, our work offers a new perspective of research on spatial evolutionary games, and provides a general formalism to study the dynamics of spatially-structured populations in biological and social contexts where individual motion is likely to affect natural selection of behavioural traits.

Sign in / Sign up

Export Citation Format

Share Document