scholarly journals Behavioral Selection Strategies of Members of Enterprise Community of Practice—An Evolutionary Game Theory Approach to the Knowledge Creation Process

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 153322-153333 ◽  
Author(s):  
Dan Wang ◽  
Baizhou Li
2014 ◽  
Vol 47 (3) ◽  
pp. 10737-10742 ◽  
Author(s):  
Fidel Torres ◽  
Cesar Garcia-Diaz ◽  
Naly Rakoto-Ravalontsalama

2012 ◽  
Vol 15 (supp01) ◽  
pp. 1250044 ◽  
Author(s):  
ADRIAN VASILE ◽  
CARMEN EUGENIA COSTEA ◽  
TANIA GEORGIA VICIU

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.


2020 ◽  
Author(s):  
Benjamin Wölfl ◽  
Hedy te Rietmole ◽  
Monica Salvioli ◽  
Frank Thuijsman ◽  
Joel S. Brown ◽  
...  

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.


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