Evolutionary game theory

![CDATA[Evolutionary Game Theory is an extension of classical Game Theory that sought to account for the properties of real-world populations of organisms and the ecosystems they inhabit, by describing the fitness-enhancing strategies maintained by the forces of evolution. Game Theory is the study and mathematical analysis of rational decision-making, typically under conditions where there are clearly defined constraints on the information one possesses and the range of available response options. The field of Game Theory is particularly concerned with modelling the possible strategies an agent may employ when engaged in games where individual success critically depends on the choices made by other players (von Neumann and Morgenstern 1944), either because other players represent opportunities for cooperation or because they are competitive rivals for some scarce resource. Since its formal, modern inception by mathematician and polymath John von Neumann 1928 (see Tucker and Luce 1959, for English translation), Game Theory has been employed in a wide range of disciplines, including computer science, moral philosophy, and extensively within behavioral science and economics (Newton 2018), owing to the insights that Game Theoretical models can offer into population-level trends that emerge spontaneously from innumerable individual agents each pursuing the most favorable outcomes they can secure for themselves. One of the earliest and most influential of these emergent phenomena is the Nash equilibrium (Nash 1951), a stable state a population reaches where no individual agent is capable of improving their outcomes by changing from their present strategy (see Gintis 2009, for a detailed overview).]]