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Relevant bibliographies by topics / Evolutionary game theory, stochastic stability

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Academic literature on the topic 'Evolutionary game theory, stochastic stability'

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Published: 14 March 2023

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Journal articles on the topic "Evolutionary game theory, stochastic stability"

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SÎRGHI, NICOLETA, and MIHAELA NEAMŢU. "DYNAMICS OF DETERMINISTIC AND STOCHASTIC EVOLUTIONARY GAMES WITH MULTIPLE DELAYS." International Journal of Bifurcation and Chaos 23, no. 07 (July 2013): 1350122. http://dx.doi.org/10.1142/s0218127413501228.

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In the present paper, we study the effect of time delays in evolutionary games with one population of users and two strategies. The case where the delays, corresponding to different strategies, are not the same is considered. The local stability of the stationary state for the replicator dynamics is analyzed. We show that there is Hopf bifurcation. The stability of the bifurcating periodic solutions is determined by using the center manifold theorem and normal form theory. The stochastic evolutionary game with delay is taken into consideration. We also study the behavior of the first and second solution moments for linear stochastic differential delay equation in the presence of white and colored noise. The last part of the paper includes numerical simulations and conclusions.

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Xu, Xiaotong, Gaocai Wang, Jintian Hu, and Yuting Lu. "Study on Stochastic Differential Game Model in Network Attack and Defense." Security and Communication Networks 2020 (June 8, 2020): 1–15. http://dx.doi.org/10.1155/2020/3417039.

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In recent years, evolutionary game theory has been gradually applied to analyze and predict network attack and defense for maintaining cybersecurity. The traditional deterministic game model cannot accurately describe the process of actual network attack and defense due to changing in the set of attack-defense strategies and external factors (such as the operating environment of the system). In this paper, we construct a stochastic evolutionary game model by the stochastic differential equation with Markov property. The evolutionary equilibrium solution of the model is found and the stability of the model is proved according to the knowledge of the stochastic differential equation. And we apply the explicit Euler numerical method to analyze the evolution of the strategy selection of the players for different problem situations. The simulation results show that the stochastic evolutionary game model proposed in this paper can get a steady state and obtain the optimal defense strategy under the action of the stochastic disturbance factor. In addition, compared with other kinds of literature, we can conclude that the return on security investment of this model is better, and the strategy selection of the attackers and defenders in our model is more suitable for actual network attack and defense.

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Song, Yang, Ron Berger, Matti Rachamim, Andrew Johnston, and Andrea Fronzetti Colladon. "Modeling the industry perspective of university-industry collaborative innovation alliances: Player behavior and stability issues." International Journal of Engineering Business Management 14 (January 2022): 184797902210972. http://dx.doi.org/10.1177/18479790221097235.

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Many firms find it challenging to develop innovations, evidenced by the ever-mounting number of university-industry research alliances. This study examines the strategic choices of actors who participate in collaborative innovation alliances involving partnerships between industry and universities (U-I) based on a stochastic evolutionary game model. White noise was introduced to reflect uncertainty and the stochastic interferences caused by the differences between actors. Using the Itô stochastic differential equation theory, we analyze stability issues of player behaviors in the evolution of a collaborative innovation alliance. The results illustrate that improvements in innovation efficiency can contribute to U-I collaborative innovation alliances. High knowledge complementarity appears to be unbeneficial to the stability of these alliances, and controlling knowledge spillovers may suppress free-rider problems from both sides of the game. Our study contributes to innovation research by providing a decision-making reference for the design of U-I cooperation.

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Zhu, Qingfeng, Rui Zong, and Mengqi Xu. "Three-Party Stochastic Evolutionary Game Analysis of Supply Chain Finance Based on Blockchain Technology." Sustainability 15, no. 4 (February 8, 2023): 3084. http://dx.doi.org/10.3390/su15043084.

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In the process of accounts receivable financing under supply chain finance, the phenomenon of accounts receivable forgery and default have caused great pressure on the supervision of financial institutions. We consider the integration of blockchain technology with a supply chain finance platform around the fraudulent default phenomenon in supply chain finance receivables financing and construct a three-party stochastic evolutionary game model among financial institutions, core enterprises, and Micro, Small, and Medium Enterprises (MSMEs). Firstly, we use Ito^’s stochastic differential equation theory to analyze the conditions for the stability of the behavior of game subjects. Secondly, we use numerical simulations to quantitatively analyze the impact of the regulatory strength of financial institutions, the information sharing of the blockchain platform, and the change of incentive parameters on the strategy choice of game subjects. Through the above analysis, we conclude that the information-sharing incentive coefficient promotes financial institutions to choose to connect to the blockchain platform, and the information-sharing risk coefficient and the regulatory intensity have the opposite effect on the blockchain platform construction. Meanwhile, the allocation of incentive shares has a significant influence on the core enterprises. Finally, we give priorities and directions for adjusting the relevant parameters to provide recommendations for financial institutions to regulate the financing process more effectively.

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Zhou, Da, Bin Wu, and Hao Ge. "Evolutionary stability and quasi-stationary strategy in stochastic evolutionary game dynamics." Journal of Theoretical Biology 264, no. 3 (June 2010): 874–81. http://dx.doi.org/10.1016/j.jtbi.2010.03.018.

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Ohtsuki, Hisashi, and Martin A. Nowak. "Evolutionary games on cycles." Proceedings of the Royal Society B: Biological Sciences 273, no. 1598 (May 23, 2006): 2249–56. http://dx.doi.org/10.1098/rspb.2006.3576.

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Traditional evolutionary game theory explores frequency-dependent selection in well-mixed populations without spatial or stochastic effects. But recently there has been much interest in studying the evolutionary game dynamics in spatial settings, on lattices and other graphs. Here, we present an analytic approach for the stochastic evolutionary game dynamics on the simplest possible graph, the cycle. For three different update rules, called ‘birth–death’ (BD), ‘death–birth’ (DB) and ‘imitation’ (IM), we derive exact conditions for natural selection to favour one strategy over another. As specific examples, we consider a coordination game and Prisoner's Dilemma. In the latter case, selection can favour cooperators over defectors for DB and IM updating. We also study the case where the replacement graph of evolutionary updating remains a cycle, but the interaction graph for playing the game is a complete graph. In this setting, all three update rules lead to identical conditions in the limit of weak selection, where we find the ‘1/3-law’ of well-mixed populations.

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Guan, Xin, Guoxing Zhang, Diyi Liu, Xu Tan, and Dong Wu. "The behavior of consumer buying new energy vehicles based on stochastic evolutionary game." Filomat 30, no. 15 (2016): 3987–97. http://dx.doi.org/10.2298/fil1615987g.

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China?s current vehicle emissions caused by air pollution problems have become increasingly prominent. How to improve new energy vehicle market share, and effectively guide the consumer buying behavior become a problem, which the government and social have to be solved. In this paper, according to establish the stochastic evolutionary game model between the government and consumers in the car market, introducing of random factors analysis on the impact of evolutionary stability ,will obtain the stable strategy of government and automotive consumers. And on the basis of it, we study the government support, cost of vehicles, the use of cost, the utility of automobile use for the ways of evolutionary stability, with case further illustrates the external disturbance factors on consumer purchase of new energy vehicles in evolutionary game process stability. Studies show that: the increasing government subsidy policy, the reducing life cycle costs of new energy vehicles and the improving effectiveness of new energy vehicles will lead the model?s evolution to the orientation of consumer purchasing new energy vehicles.

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Helbing, Dirk. "A stochastic behavioral model and a ?Microscopic? foundation of evolutionary game theory." Theory and Decision 40, no. 2 (March 1996): 149–79. http://dx.doi.org/10.1007/bf00133171.

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Zhang, Jinxin, and Meng Wu. "Cooperation Mechanism in Blockchain by Evolutionary Game Theory." Complexity 2021 (November 8, 2021): 1–9. http://dx.doi.org/10.1155/2021/1258730.

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In the blockchain network, to get rewards in the blockchain, blockchain participants pay for various forms of competition such as computing power, stakes, and other resources. Because of the need to pay a certain cost, individual participants cooperate to maintain the long-term stability of the blockchain jointly. In the course of such competition, the game between each other has appeared invisibly. To better understand the blockchain design of cooperation mechanisms, in this paper, we constructed a game framework between participants with different willingness, using evolutionary game theory, and complex network games. We analyzed how the behavior of participants potentially develops with cost and payoff. We consider the expected benefits of participants for the normal growth of the blockchain as the major factor. Considering the behavior of malicious betrayers, the blockchain needs to be maintained in the early stage. Numerical simulation supports our analysis.

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Brown, Joel S. "Why Darwin would have loved evolutionary game theory." Proceedings of the Royal Society B: Biological Sciences 283, no. 1838 (September 14, 2016): 20160847. http://dx.doi.org/10.1098/rspb.2016.0847.

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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.

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Dissertations / Theses on the topic "Evolutionary game theory, stochastic stability"

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Matros, Alexander. "Stochastic stability and equilibrium selection in games." Doctoral thesis, Stockholm : Economic Research Institute, Stockholm School of Economics (Ekonomiska forskningsinstitutet vid Handelshögsk.) (EFI), 2001. http://www.hhs.se/efi/summary/571.htm.

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vicario, eugenio. "Essays on Segregation, Minorities, and Imitation." Doctoral thesis, Università di Siena, 2020. http://hdl.handle.net/11365/1107924.

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The thesis is composed by three chapters. The common theme of the three essays is the identification of long run equilibria of games played on regular networks where interactions are at local level. In the first and second chapter I contribute to distinct literatures applying technics and results from the literature on evolutionary game theory with local interactions. The study of economic segregation within towns, and the tendency of ethnic minorities to live in ethnic enclaves are at the center of the first and the second chapter respectively. In the third chapter a refinement of previous results in the theoretical literature on evolutionary game theory with local interactions is given. In the thesis I develop models with different specifications of revision opportunities, error models, and behavior of agents, which require different techniques for the selection of the long run equilibria. The spatial structure is common to the three chapters, in fact agents are deployed on lattices with periodic boundary conditions. In the first chapter the spatial structure is given by a two dimensional lattice, i.e a torus, in the third chapter a one dimensional lattice, i.e. a ring, is used, while in the second chapter I use both the specifications. The network is always fixed and exogenously given, and the concept of continuous neighborhood is used. Neighborhoods are said to be continuous when are based on the individual perception of agents. Each agent is in the middle of his own neighborhood, and then the neighborhoods of different agents may partially overlap but never coincide. This in contrast with the concept of bounded neighborhoods where agents belonging to the same neighborhood share all the neighbors. In this last case neighborhoods form a partition of the set of agents. Following the literature on continuous neighborhood the two main specifications are considered, in fact are used both the Moore and the Von Neumann neighborhoods in the two dimensional lattice. In the one dimensional lattice models different dimensions of the neighborhood are considered. In the first chapter agents move within the network exchanging position each other. In every period two agents are selected and switch position if both will be better off in the new neighborhood. Differently in the second and third chapter agents do not move within the network while instead they revise their strategy based on the strategies of neighbors. The timing of revision opportunities is another fundamental ingredient of the three models. In the first and the second chapter asynchronous revision opportunities are modeled, in fact in the first chapter only one couple per time has the possibility to switch position, while in the second chapter only one agent per turn revises the strategy. In the third chapter the revision opportunities are simultaneous, and all the agents revise their strategy in each period. In the three chapter, as usual in evolutionary game theory, agents have bounded rationality. In fact agents have a myopic behavior, they are unable to make any prevision about the future states, and then revise their strategy only considering the actual state. In the third chapter a further level of irrationality is given by the fact that agents, instead of best replying to the actual situation, as in the first and second chapter, imitate the action of the best performing neighbor. A stochastically stable state is a state that is observed with a positive probability in the long run in presence of a small perturbation. The perturbation is at the individual level, in fact each agent, in every moment, has a small but positive chance to make a decision differently from that prescribed by his behavioral rule. The perturbation in biology is used to model mutations, while in economics the noise is represented by mistakes and experimentations. Through the introduction of a small amount of noise is possible to define a perturbed transition matrix for which is possible to move from any state of the world to any other in a finite number of steps. In the first chapter the behavior of agents is described by a logit choice function, for which costly mistakes are less likely. Each agent has a positive probability to accept or not an exchange, depending on the variation of utility obtained with the exchange. The game can be described by a potential function defined on the set of strategies of agents, for which every change in the utility of agents is reflected in a variation of the potential function. Assuming the logit choice rule and in the presence of asynchronous revision opportunities, in a potential game the stochastically stable states coincide with states having maximum potential. In this setting is sufficient to study the potential function to select the set of long run equilibria. In the second and third chapter a uniform error model is implemented. Each error can occur with the same probability, independently from how costly it is. In the second chapter three versions of the model are developed. In the first version there is not a spatial structure and interactions are at the global level. The identification of stochastically stable states is obtained using the technique developed by Young (1993), based on results by Freidlin and Wentzell (1984). At the basis of this technique there is the construction of rooted trees, made by the least resistance paths from each absorbing set to each other, where an absorbing set is a minimal set from which the unperturbed process can not escape. Between the paths connecting an absorbing set to another one the least resistance path is the one that is more likely to be observed. The summation of the resistance of all the least resistance paths ending in an absorbing set, E, and starting from all the other absorbing sets is the stochastic potential of the absorbing set E. The absorbing sets with minimal stochastic potential are the stochastically stable sets. The application is relatively simple having only two absorbing sets connected by only one path. In the second version of the model agents are deployed on a two dimensional lattice and interact only with a set of neighbors and the result is obtained via simulations. There are many advantages in the use of simulations, but also some limitations. In fact when the probability of a transition out from an absorbing set is very low it is unlikely to observe it during a simulation, and may be difficult to asses which transition is more likely. When the error rate is higher transitions are more likely but the perturbation may affect too much the dynamics. In the third version agents are deployed on one dimensional lattice, as in the third chapter. The radius coradius technique proposed by Ellison (2000) is used to identify the stochastically stable sets. The basic idea is to compute the radius and the coradius of all the absorbing sets and compare them. The radius represents how is difficult to leave the basin of attraction of an absorbing set, while the difficulty to enter into the basin of attraction of an absorbing set is measured by the coradius. The stochastically stable set of the model is contained in the subset of absorbing sets having radius greater then coradius.

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Josephson, Jens. "Evolution and learning in games." Doctoral thesis, Stockholm : Economic Research Institute, Stockholm School of Economics (Ekonomiska forskningsinstitutet vid Handelshögsk.) (EFI), 2001. http://www.hhs.se/efi/summary/587.htm.

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4

Treacy, Brian. "A stochastic differential equation derived from evolutionary game theory." Thesis, Uppsala universitet, Analys och sannolikhetsteori, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-377554.

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RADI, Davide. "Essays on Nonlinear Dynamics, Heterogeneous Agents and Evolutionary Games in Economics and Finance." Doctoral thesis, Università degli studi di Bergamo, 2014. http://hdl.handle.net/10446/30390.

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Marquitti, Flávia Maria Darcie. "Parasitas de interações e a coevolução de mutualismos." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/41/41134/tde-14012016-162055/.

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Mutualismos são interações em que os parceiros se exploram reciprocamente com benefícios líquidos para ambos os indivíduos que interagem. Sistemas mutualistas multiespecíficos podem ser descritos como redes de interação, tais como aquelas formadas por sistemas de polinização, dispersão de sementes, estações de limpeza em ambientes recifais, formigas defensoras de plantas, mimetismo mülleriano e bactérias fixadoras de nitrogênio em raízes de plantas. As interações mutualísticas estão sujeitas à trapaça por indivíduos que, por meio de algum comportamento, alcançam o benefício oferecido pelo parceiro sem oferecer nada ou oferecer muito pouco em troca. No entanto, interações mutualísticas persistem apesar da existência de trapaceiros. Neste trabalho, mostro que os parasitas de interações mutualísticas, os trapaceiros, aumentam a resiliência das redes mutualísticas às perturbações mais rapidamente em redes aninhadas, redes tipicamente encontradas em mutualismos ricos em espécies. Portanto os efeitos combinados de trapaceiros, estrutura e dinâmica das redes mutualísticas podem ter implicações para a forma como a biodiversidade é mantida. Em seguida, estudo as condições em que flores tubulares, que sofrem maiores danos ao interagirem com ladrões de néctar, conseguem coexistir com flores planares, polinizadores e pilhadores por meio de efeitos indiretos da trapaça em seu sucesso reprodutivo. O roubo do néctar pode aumentar o sucesso de uma planta se as interações com pilhadores gerarem maior quantidade de polinização cruzada, aumentando assim o sucesso reprodutivo das plantas que interagem com ambos os visitantes florais. Tal resultado sugere uma nova fonte de manutenção da cooperação e da diversidade de estratégias por meio de efeitos não lineares das interações entre diferentes estratégias. Finalmente, estudo como as interações locais promovem a prevalência de mímicos (trapaceiros) em uma certa população na ausência de seus modelos. Mostro que presas que interagem localmente podem favorecer a predominância de mímicos e predadores que os evitam após algumas gerações e que uma distribuição não aleatória de indivíduos no espaço pode reforçar ainda mais este efeito inesperado de alopatria de modelo e mímico
Mutualisms are interactions in which organisms of different species exploit each other with net benefits for both interacting individuals. Multispecific mutualistic system can be depicted as interaction networks, such as those formed by plant-pollinator interactions, dispersal systems, species interacting in cleaning stations in reef environments, protective ants in plants, müllerian mimicry, and nitrogen fixing bacteria on the roots of plants. Mutualistic interaction is subject to cheating by individuals who, by means of a diversity of behavioral strategies, achieve the benefit provided by the partner offering nothing or few in return. However, the mutualistic interactions persist despite the existence of cheaters. In this work I show that the parasites of mutualistic interactions increase the resilience of mutualistic networks to disturbances in nested networks, typically found in species-rich mutualisms. Therefore the joint effect of cheating, structure and dynamics of mutualistic networks have implications for how biodiversity is maintained. I subsequently study the conditions under which tubular flowers, which suffer stronger damages when interacting with nectar robbers, can coexist with planar flowers, pollinators, and robbers through indirect effects of cheating on their reproductive success. The theft of nectar may increase the success of a plant if its interactions with robbers generate higher degrees of cross-pollination, thus increasing the reproductive success of plants that interact with both floral visitors. This study suggests a new source of continued cooperation and diversity strategies through non-linear effects of the interactions between different strategies. Finally, I study how local interactions can promote the prevalence of mimic (the cheaters) in a given population in the absence of their models. I found that prey interacting locally may favor the predominance of mimic preys and avoid predators that, after a few generations and under a non-random distribution of individuals in space, can further strengthen this unexpected effect allopatry of the mimic and its model

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Palmigiani, Davide. "Stochastic models for biological evolution." Doctoral thesis, 2019. http://hdl.handle.net/11573/1243790.

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In this work, we deal with the problem of creating a model that describes a population of agents undergoing Darwinian Evolution, which takes into account the basic phenomena of this process. According to the principles of evolutionary biology, Evolution occurs if there is selection and adaptation of phenotypes, mutation of genotypes, presence of physical space. The evolution of a biological population is then described by a system of ordinary stochastic differential equations; the basic model of dynamics represents the trend of a population divided into different types, with relative frequency in a simplex. The law governing this dynamics is called Replicator Dynamics: the growth rate of type k is measured in terms of evolutionary advantage, with its own fitness compared to the average in the population. The replicator dynamics model turns into a stochastic process when we consider random mutations that can transform fractions of individuals into others. The two main forces of Evolution, selection and mutation, act on different layers: the environment acts on the phenotype, selecting the fittest, while the randomness of the mutations affects the genotype. This difference is underlined in the model, where each genotype express a phenotype, and fitness influences emerging traits, not explicitly encoded in genotypes. The presence of a potentially infinite space of available genomes makes sure that variants of individuals with characteristics never seen before can be generated. In conclusion, numerical simulations are provided for some applications of the model, such as a variation of Conway's Game of Life

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Books on the topic "Evolutionary game theory, stochastic stability"

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Bomze, Immanuel M. Game theoretical foundations of evolutionary stability. Berlin: Springer-Verlag, 1989.

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Cressman, Ross, ed. The Stability Concept of Evolutionary Game Theory. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-49981-4.

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The stability concept of evolutionary game theory: A dynamic approach. Berlin: Springer-Verlag, 1992.

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Cressman, Ross. Stability Concept of Evolutionary Game Theory: A Dynamic Approach. Springer London, Limited, 2013.

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Equity, Efficiency and Evolutionary Stability in Bargaining Games with Joint Production. Springer, 2000.

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Königstein, Manfred. Equity, Efficiency and Evolutionary Stability in Bargaining Games with Joint Production. Springer London, Limited, 2012.

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Chen, Bor-Sen. Systems Evolutionary Biology: Biological Network Evolution Theory, Stochastic Evolutionary Game Strategies, and Applications to Systems Synthetic Biology. Elsevier Science & Technology, 2018.

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Chen, Bor-Sen. Systems Evolutionary Biology: Biological Network Evolution Theory, Stochastic Evolutionary Game Strategies, and Applications to Systems Synthetic Biology. Elsevier Science & Technology Books, 2018.

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Book chapters on the topic "Evolutionary game theory, stochastic stability"

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Fujiwara-Greve, Takako. "Evolutionary Stability $$^*$$ ∗." In Non-Cooperative Game Theory, 217–46. Tokyo: Springer Japan, 2015. http://dx.doi.org/10.1007/978-4-431-55645-9_10.

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Baron, Richard, Jacques Durieu, Hans Haller, and Philippe Solal. "Stochastic Evolutionary Game Theory." In Cognitive Economics, 267–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24708-1_16.

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van Damme, Eric. "Evolutionary Game Theory." In Stability and Perfection of Nash Equilibria, 208–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-96978-2_9.

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van Damme, Eric. "9 Evolutionary Game Theory." In Stability and Perfection of Nash Equilibria, 214–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58242-4_9.

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Chung, Christine, and Evangelia Pyrga. "Stochastic Stability in Internet Router Congestion Games." In Algorithmic Game Theory, 183–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04645-2_17.

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Cressman, Ross. "Introduction." In The Stability Concept of Evolutionary Game Theory, 1–3. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-49981-4_1.

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Cressman, Ross. "Frequency-Dependent Evolution in a Single Haploid Species." In The Stability Concept of Evolutionary Game Theory, 4–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-49981-4_2.

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Cressman, Ross. "Frequency-Dependent Evolution in a Two-Species Haploid System." In The Stability Concept of Evolutionary Game Theory, 31–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-49981-4_3.

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Cressman, Ross. "Frequency-Dependent Evolution in a Randomly-Mating Diploid Species." In The Stability Concept of Evolutionary Game Theory, 57–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-49981-4_4.

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Cressman, Ross. "Frequency- and Density-Dependent Evolution in a Haploid Species." In The Stability Concept of Evolutionary Game Theory, 77–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-49981-4_5.

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Conference papers on the topic "Evolutionary game theory, stochastic stability"

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Molzon, Robert. "Deterministic approximation of stochastic evolutionary dynamics." In 2009 International Conference on Game Theory for Networks (GameNets). IEEE, 2009. http://dx.doi.org/10.1109/gamenets.2009.5137417.

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Kojima, Taichi, and Sumiko Miyata. "Flow Admission Control Method with Bounded Rationality Using Stochastic Evolutionary Game Theory." In GLOBECOM 2021 - 2021 IEEE Global Communications Conference. IEEE, 2021. http://dx.doi.org/10.1109/globecom46510.2021.9685626.

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Gammon, Mark, Abdi Kukner, and Ahmet Alkan. "Hull Form Optimization of Performance Characteristics of Turkish Gulets for Charter." In SNAME 17th Chesapeake Sailing Yacht Symposium. SNAME, 2005. http://dx.doi.org/10.5957/csys-2005-006.

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Turkish Gulets are motor-sailors that are still being built using wooden boatbuilding traditional construction in the Aegean and Mediterranean as well as being built using steel and cold moulded techniques. They are typical of the craft used for skippered charter tours in the region and exhibit good seakeeping in the shorter steep sea of the Mediterranean and also for manoeuvring in port and in anchorages. Usually this performance is at the cost of resistance. Sailing performance and stability are surprisingly not considered due to the large beams. The hull forms of two typical gulets are used to examine the stability, resistance and coupled heave and pitch. A multi-objective evolutionary optimization methodology is used to investigate the performance of the three objectives. The evaluation of resistance uses a transom modified Michell theory in keeping with the smaller L/B ratios and large transoms of many of these vessel types. Seakeeping is evaluated using a strip motion program and the stability curve is used to provide a stability index. The multi-objective analysis is based on the optimization capabilities of genetic algorithms. Evolutionary algorithms are stochastic in nature and follow the Darwinian principle of survival of the fittest. From a given population of hull candidates, those hulls that are “fitter” by having better resistance, seakeeping and stability are selected to generate a new population. Over the course of many generations, the hulls are optimized to provide better performance. Each of the objectives requires an index to measure the performance of the candidate.

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