scholarly journals Evolutionary dynamics in structured populations

2010 ◽  
Vol 365 (1537) ◽  
pp. 19-30 ◽  
Author(s):  
Martin A. Nowak ◽  
Corina E. Tarnita ◽  
Tibor Antal
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Evolutionary Dynamics ◽  
Evolutionary Game ◽  
Evolutionary Process ◽  
Structured Populations ◽  
Evolution Of Cooperation ◽  
Evolutionary Graph Theory ◽  
Phenotype Space ◽  
Multicellular Organisms

Evolutionary dynamics shape the living world around us. At the centre of every evolutionary process is a population of reproducing individuals. The structure of that population affects evolutionary dynamics. The individuals can be molecules, cells, viruses, multicellular organisms or humans. Whenever the fitness of individuals depends on the relative abundance of phenotypes in the population, we are in the realm of evolutionary game theory. Evolutionary game theory is a general approach that can describe the competition of species in an ecosystem, the interaction between hosts and parasites, between viruses and cells, and also the spread of ideas and behaviours in the human population. In this perspective, we review the recent advances in evolutionary game dynamics with a particular emphasis on stochastic approaches in finite sized and structured populations. We give simple, fundamental laws that determine how natural selection chooses between competing strategies. We study the well-mixed population, evolutionary graph theory, games in phenotype space and evolutionary set theory. We apply these results to the evolution of cooperation. The mechanism that leads to the evolution of cooperation in these settings could be called ‘spatial selection’: cooperators prevail against defectors by clustering in physical or other spaces.

scholarly journals Evolution of cooperation in an epithelium

2019 ◽  
Vol 16 (152) ◽  
pp. 20180918 ◽  
Author(s):  
Jessie Renton ◽  
Karen M. Page
Keyword(s):  
Social Interactions ◽  
Voronoi Tessellation ◽  
Evolutionary Game ◽  
Cellular Level ◽  
Structured Populations ◽  
Evolution Of Cooperation ◽  
Animal Kingdom ◽  
Population Structures ◽  
Fixation Probabilities ◽  
Evolutionary Graph Theory

Cooperation is prevalent in nature, not only in the context of social interactions within the animal kingdom but also on the cellular level. In cancer, for example, tumour cells can cooperate by producing growth factors. The evolution of cooperation has traditionally been studied for well-mixed populations under the framework of evolutionary game theory, and more recently for structured populations using evolutionary graph theory (EGT). The population structures arising due to cellular arrangement in tissues, however, are dynamic and thus cannot be accurately represented by either of these frameworks. In this work, we compare the conditions for cooperative success in an epithelium modelled using EGT, to those in a mechanical model of an epithelium—the Voronoi tessellation (VT) model. Crucially, in this latter model, cells are able to move, and birth and death are not spatially coupled. We calculate fixation probabilities in the VT model through simulation and an approximate analytic technique and show that this leads to stronger promotion of cooperation in comparison with the EGT model.

scholarly journals Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations

2014 ◽  
Vol 4 (4) ◽  
pp. 20140037 ◽  
Author(s):  
David Liao ◽  
Thea D. Tlsty
Keyword(s):  
Game Theory ◽  
Population Dynamics ◽  
Evolutionary Game Theory ◽  
Evolutionary Dynamics ◽  
Evolutionary Game ◽  
Treatment Strategies ◽  
Analysis Method ◽  
Analysis Techniques ◽  
Game Theoretic ◽  
And Control

Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.

AN EVOLUTIONARY GAME THEORY APPROACH TO MARKET COMPETITION AND COOPERATION

2012 ◽  
Vol 15 (supp01) ◽  
pp. 1250044 ◽  
Author(s):  
ADRIAN VASILE ◽  
CARMEN EUGENIA COSTEA ◽  
TANIA GEORGIA VICIU
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Market Competition ◽  
Evolutionary Game ◽  
Evolutionary Process ◽  
Interdisciplinary Approach ◽  
Market Potential ◽  
Theory Approach ◽  
Open Market ◽  
Additional Information

Evolutionary game theory can be attested as a practical apparatus in providing additional information on the workings of the open market and on the blueprint for dynamics in economic phenomena. Through an interdisciplinary approach to different game scenarios, the dependencies among market forces are observed, thus, being capable of offering insight on the incentives for adopting different behaviors. This paper takes use of the different factors that form the payoff of certain strategies which can be adopted by companies, and determines the prerequisites for cooperation or competition while all together constructing settings and predictions on the evolution of the phenomena. Determining the evolutionary stable strategy for different scenarios and looking at the way in which the probability of encountering a certain behavior is constructed, provide the possibility to determine the outcome of an ongoing evolutionary process. By studying the monotony of the probability function in respect to each of the factors that contribute to the payoffs, the study indicates that there is a positive relation between the percentage of population playing competitive strategies and market potential, costs, and risks of penalty for cooperation and a negative relation between this percentage and the disputed market share and supplementary winnings from arrangements.

scholarly journals Fisheries management as a Stackelberg Evolutionary Game: Finding an evolutionarily enlightened strategy

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245255
Author(s):  
Monica Salvioli ◽  
Johan Dubbeldam ◽  
Kateřina Staňková ◽  
Joel S. Brown
Keyword(s):  
Game Theory ◽  
Fisheries Management ◽  
Evolutionary Game Theory ◽  
Evolutionary Dynamics ◽  
Evolutionary Game ◽  
Fish Population ◽  
Stackelberg Equilibrium ◽  
Negative Effects ◽  
Evolutionary Changes ◽  
Body Sizes

Fish populations subject to heavy exploitation are expected to evolve over time smaller average body sizes. We introduce Stackelberg evolutionary game theory to show how fisheries management should be adjusted to mitigate the potential negative effects of such evolutionary changes. We present the game of a fisheries manager versus a fish population, where the former adjusts the harvesting rate and the net size to maximize profit, while the latter responds by evolving the size at maturation to maximize the fitness. We analyze three strategies: i) ecologically enlightened (leading to a Nash equilibrium in game-theoretic terms); ii) evolutionarily enlightened (leading to a Stackelberg equilibrium) and iii) domestication (leading to team optimum) and the corresponding outcomes for both the fisheries manager and the fish. Domestication results in the largest size for the fish and the highest profit for the manager. With the Nash approach the manager tends to adopt a high harvesting rate and a small net size that eventually leads to smaller fish. With the Stackelberg approach the manager selects a bigger net size and scales back the harvesting rate, which lead to a bigger fish size and a higher profit. Overall, our results encourage managers to take the fish evolutionary dynamics into account. Moreover, we advocate for the use of Stackelberg evolutionary game theory as a tool for providing insights into the eco-evolutionary consequences of exploiting evolving resources.

scholarly journals Evolution of cooperation in evolutionary games for Sanitation Boards

2014 ◽  
Vol 17 (2) ◽  
Author(s):  
Rocío Botta ◽  
Gerardo Blanco ◽  
Christian E. Schaerer
Keyword(s):  
Game Theory ◽  
Public Good ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Evolution Of Cooperation ◽  
Cost Models ◽  
Policy Makers ◽  
Community Projects ◽  
The Cost

In a group of individuals that come together to produce a good or provide a service, the cooperators (who pay to produce the good) are often exploited by those who receive the benefit without paying the cost. Models were developed over time using incentives (reward or punishment) and the option of abandoning the initiative to promote and stabilize the cooperation. In this paper we analyze several models based on the evolutionary game theory and public good games. We compare and organize them in a taxonomic table following their main characteristics to select the most suitable for a specific problem. The analyzed models are compared by using a public good problem in community projects for water supply. We have reasonable assurance that phenomena that appear on mod- els also occurs in these community projects. Therefore, we propose that evolutionary game theory can be a useful tool for policy-makers in order to improve cooperation and discourage defection in sanitation boards.

scholarly journals The contribution of evolutionary game theory to understanding and treating cancer

2020 ◽  
Author(s):  
Benjamin Wölfl ◽  
Hedy te Rietmole ◽  
Monica Salvioli ◽  
Frank Thuijsman ◽  
Joel S. Brown ◽  
...  
Keyword(s):  
Game Theory ◽  
Cancer Progression ◽  
Evolutionary Game Theory ◽  
Cancer Biology ◽  
Evolutionary Dynamics ◽  
Evolutionary Game ◽  
Great Promise ◽  
Full Potential ◽  
Theory Approach ◽  
Game Theoretic

AbstractEvolutionary game theory mathematically conceptualizes and analyzes biological interactions where one’s fitness not only depends on one’s own traits, but also on the traits of others. Typically, the individuals are not overtly rational and do not select, but rather, inherit their traits. Cancer can be framed as such an evolutionary game, as it is composed of cells of heterogeneous types undergoing frequency-dependent selection. In this article, we first summarize existing works where evolutionary game theory has been employed in modeling cancer and improving its treatment. Some of these game-theoretic models suggest how one could anticipate and steer cancer’s eco-evolutionary dynamics into states more desirable for the patient via evolutionary therapies. Such therapies offer great promise for increasing patient survival and decreasing drug toxicity, as demonstrated by some recent studies and clinical trials. We discuss clinical relevance of the existing game-theoretic models of cancer and its treatment, and opportunities for future applications. We discuss the developments in cancer biology that are needed to better utilize the full potential of game-theoretic models. Ultimately, we demonstrate that viewing tumors with an evolutionary game theory approach has medically useful implications that can inform and create a lockstep between empirical findings, and mathematical modeling. We suggest that cancer progression is an evolutionary game and needs to be viewed as such.

scholarly journals Why Darwin would have loved evolutionary game theory

2016 ◽  
Vol 283 (1838) ◽  
pp. 20160847 ◽  
Author(s):  
Joel S. Brown
Keyword(s):  
Game Theory ◽  
Natural Selection ◽  
Evolutionary Game Theory ◽  
Evolutionary Dynamics ◽  
Evolutionary Game ◽  
Scientific Basis ◽  
Matrix Games ◽  
Form And Function ◽  
Heritable Phenotype ◽  
And Function

Humans have marvelled at the fit of form and function, the way organisms' traits seem remarkably suited to their lifestyles and ecologies. While natural selection provides the scientific basis for the fit of form and function, Darwin found certain adaptations vexing or particularly intriguing: sex ratios, sexual selection and altruism. The logic behind these adaptations resides in frequency-dependent selection where the value of a given heritable phenotype (i.e. strategy) to an individual depends upon the strategies of others. Game theory is a branch of mathematics that is uniquely suited to solving such puzzles. While game theoretic thinking enters into Darwin's arguments and those of evolutionists through much of the twentieth century, the tools of evolutionary game theory were not available to Darwin or most evolutionists until the 1970s, and its full scope has only unfolded in the last three decades. As a consequence, game theory is applied and appreciated rather spottily. Game theory not only applies to matrix games and social games, it also applies to speciation, macroevolution and perhaps even to cancer. I assert that life and natural selection are a game, and that game theory is the appropriate logic for framing and understanding adaptations. Its scope can include behaviours within species, state-dependent strategies (such as male, female and so much more), speciation and coevolution, and expands beyond microevolution to macroevolution. Game theory clarifies aspects of ecological and evolutionary stability in ways useful to understanding eco-evolutionary dynamics, niche construction and ecosystem engineering. In short, I would like to think that Darwin would have found game theory uniquely useful for his theory of natural selection. Let us see why this is so.

On the Original Contract: Evolutionary Game Theory and Human Evolution

2005 ◽  
Vol 27 (1) ◽  
Author(s):  
Alex Rosenberg ◽  
Stefan Linquist
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Gene Sequence ◽  
Sequence Data ◽  
Evolutionary Game ◽  
Gene Sequencing ◽  
Evolution Of Cooperation ◽  
Biological Anthropology ◽  
Original Contract ◽  
Gene Sequence Data

AbstractThis paper considers whether the available evidence from archeology, biological anthropology, primatology, and comparative gene-sequencing, can test evolutionary game theory models of cooperation as historical hypotheses about the actual course of human prehistory. The examination proceeds on the assumption that cooperation is the product of cultural selection and is not a genetically encoded trait. Nevertheless, we conclude that gene sequence data may yet shed significant light on the evolution of cooperation.

scholarly journals Evolutionary game theoretic resource allocation simulation for molecular communication

2021 ◽  
Vol 2 (3) ◽  
pp. 111-119
Author(s):  
Caglar Koca ◽  
Meltem Civas ◽  
Ozgur B. Akan
Keyword(s):  
Game Theory ◽  
Resource Allocation ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Evolutionary Process ◽  
Molecular Communication ◽  
Transmission Performance ◽  
Game Theoretic ◽  
Selection Of ◽  
Evolution Approach

Molecular Communication (MC) is an emerging technology using molecules to transfer information between nanomachines. In this paper, we approach the resource allocation problem in Molecular Nano-networks (MCN) from the perspective of evolutionary game theory. In particular, we consider an MCN as an organism having three types of nodes acting as a sensor, relay, and sink, respectively. The resources are distributed among the nodes according to an evolutionary process, which relies on the selection of the most successful organisms followed by creating their offspring iteratively. In this regard, the success of an organism is measured by the total number of dropped messages during its life cycle. To illustrate the evolution procedure, we design a toy problem, and then solve it analytically and using the evolution approach for comparison. We further simulate the performance of the evolution approach on randomly generated organisms. The results reveal the potential of evolutionary game theory tools to improve the transmission performance of MCNs.

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