572 research outputs found
Existence of Evolutionarily Stable Strategies Remains Hard to Decide for a Wide Range of Payoff Values
The concept of an evolutionarily stable strategy (ESS), introduced by Smith
and Price, is a refinement of Nash equilibrium in 2-player symmetric games in
order to explain counter-intuitive natural phenomena, whose existence is not
guaranteed in every game. The problem of deciding whether a game possesses an
ESS has been shown to be -complete by Conitzer using the
preceding important work by Etessami and Lochbihler. The latter, among other
results, proved that deciding the existence of ESS is both NP-hard and
coNP-hard. In this paper we introduce a "reduction robustness" notion and we
show that deciding the existence of an ESS remains coNP-hard for a wide range
of games even if we arbitrarily perturb within some intervals the payoff values
of the game under consideration. In contrast, ESS exist almost surely for large
games with random and independent payoffs chosen from the same distribution.Comment: 24 pages, 4 figure
Evolutionary games on graphs
Game theory is one of the key paradigms behind many scientific disciplines
from biology to behavioral sciences to economics. In its evolutionary form and
especially when the interacting agents are linked in a specific social network
the underlying solution concepts and methods are very similar to those applied
in non-equilibrium statistical physics. This review gives a tutorial-type
overview of the field for physicists. The first three sections introduce the
necessary background in classical and evolutionary game theory from the basic
definitions to the most important results. The fourth section surveys the
topological complications implied by non-mean-field-type social network
structures in general. The last three sections discuss in detail the dynamic
behavior of three prominent classes of models: the Prisoner's Dilemma, the
Rock-Scissors-Paper game, and Competing Associations. The major theme of the
review is in what sense and how the graph structure of interactions can modify
and enrich the picture of long term behavioral patterns emerging in
evolutionary games.Comment: Review, final version, 133 pages, 65 figure
The influence of topology and information diffusion on networked game dynamics
This thesis studies the influence of topology and information diffusion on the strategic interactions of agents in a population. It shows that there exists a reciprocal relationship between the topology, information diffusion and the strategic interactions of a population of players. In order to evaluate the influence of topology and information flow on networked game dynamics, strategic games are simulated on populations of players where the players are distributed in a non-homogeneous spatial arrangement. The initial component of this research consists of a study of evolution of the coordination of strategic players, where the topology or the structure of the population is shown to be critical in defining the coordination among the players. Next, the effect of network topology on the evolutionary stability of strategies is studied in detail. Based on the results obtained, it is shown that network topology plays a key role in determining the evolutionary stability of a particular strategy in a population of players. Then, the effect of network topology on the optimum placement of strategies is studied. Using genetic optimisation, it is shown that the placement of strategies in a spatially distributed population of players is crucial in maximising the collective payoff of the population. Exploring further the effect of network topology and information diffusion on networked games, the non-optimal or bounded rationality of players is modelled using topological and directed information flow of the network. Based on the topologically distributed bounded rationality model, it is shown that the scale-free and small-world networks emerge in randomly connected populations of sub-optimal players. Thus, the topological and information theoretic interpretations of bounded rationality suggest the topology, information diffusion and the strategic interactions of socio-economical structures are cyclically interdependent
The influence of topology and information diffusion on networked game dynamics
This thesis studies the influence of topology and information diffusion on the strategic interactions of agents in a population. It shows that there exists a reciprocal relationship between the topology, information diffusion and the strategic interactions of a population of players. In order to evaluate the influence of topology and information flow on networked game dynamics, strategic games are simulated on populations of players where the players are distributed in a non-homogeneous spatial arrangement. The initial component of this research consists of a study of evolution of the coordination of strategic players, where the topology or the structure of the population is shown to be critical in defining the coordination among the players. Next, the effect of network topology on the evolutionary stability of strategies is studied in detail. Based on the results obtained, it is shown that network topology plays a key role in determining the evolutionary stability of a particular strategy in a population of players. Then, the effect of network topology on the optimum placement of strategies is studied. Using genetic optimisation, it is shown that the placement of strategies in a spatially distributed population of players is crucial in maximising the collective payoff of the population. Exploring further the effect of network topology and information diffusion on networked games, the non-optimal or bounded rationality of players is modelled using topological and directed information flow of the network. Based on the topologically distributed bounded rationality model, it is shown that the scale-free and small-world networks emerge in randomly connected populations of sub-optimal players. Thus, the topological and information theoretic interpretations of bounded rationality suggest the topology, information diffusion and the strategic interactions of socio-economical structures are cyclically interdependent
Cruel to be kind: The role of the evolution of altruistic punishment in sustaining human cooperation in public goods games
People cooperate in public goods games even when an individual’s utility maximizing strategy is to defect. A form of non-institutionalized punishment called altruistic punishment—or strong reciprocity—may explain this cooperative behavior. I consider laboratory experiments of public goods games that provide evidence of altruistic punishment and proximate explanations for that behavior. I also present theories of the evolution of altruistic punishment via group-selection, multi-level selection, and gene and culture co-evolution. Furthermore, I consider criticisms of both laboratory results and evolutionary theories that suggest weaknesses in the current research on altruistic punishment. In sum, we will likely never have a definitive explanation of the origins and evolution of human cooperation. I conclude, however, that altruistic punishment may form an integral part of that trajectory
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