Multiple Steady States, Limit Cycles and Chaotic Attractors in Evolutionary Games with Logit Dynamics

This paper investigates, by means of simple, three and four strategy games, the occurrence of periodic and chaotic behaviour in a smooth version of the Best Response Dynamics, the Logit Dynamics. The main finding is that, unlike Replicator Dynamics, generic Hopf bifurcation and thus, stable limit cycles, do occur under the Logit Dynamics, even for three strategy games. Moreover, we show that the Logit Dynamics displays another bifurcation which cannot to occur under the Replicator Dynamics: the fold catastrophe. Finally, we find, in a four strategy game, a period-doubling route to chaotic dynamics under a 'weighted' version of the Logit Dynamics.

Multiple equilibria and limit cycles in evolutonary games with Logit Dynamics

This note shows, by means of two simple, three-strategy games, the existence of stable periodic orbits and of multiple, interior steady states in a smooth version of the Best-Response Dynamics, the Logit Dynamics. The main finding is that, unlike Replicator Dynamics, generic Hopf bifurcation and thus, stable limit cycles, occur under the Logit Dynamics, even for three-strategy games. We also show that the Logit Dynamics displays another bifurcation which cannot occur under the Replicator Dynamics: the fold bifurcation, with non-monotonic creation and disappearance of steady states

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

Cycles and Instability in a Rock-Paper-Scissors Population Game: A Continuous Time Experiment

We report laboratory experiments that use new, visually oriented software to explore the dynamics of 3×3 games with intransitive best responses. Each moment, each player is matched against the entire population, here 8 human subjects. A “heat map” offers instantaneous feedback on current profit opportunities. In the continuous slow adjustment treatment, we see distinct cycles in the population mix. The cycle amplitude, frequency and direction are consistent with the standard learning models. Cycles are more erratic and higher frequency in the instantaneous adjustment treatment. Control treatments (using simultaneous matching in discrete time) replicate previous results that exhibit weak or no cycles. Average play is approximated fairly well by Nash equilibrium, and an alternative point prediction, “TASP” (Time Average of the Shapley Polygon), captures some regularities that Nash equilibrium misses

Adaptive Behavior in Continuous Time

This research investigates population-level behavioral dynamics, how they affect the emergence of self-enforcing conventions, and how they can aid in the design of mechanisms to better achieve policy goals. It seeks to identify why long-run behavior approaches equilibrium in some environments, and fails to do so in others. This question is important because equilibrium is frequently employed to make policy recommendations, so it is necessary to identify when it provides reliable predictions. Further, many strategic environments only reach equilibrium in the long run, so modeling the short run process from which long run equilibria eventually emerge can help answer important policy-relevant questions. To answer these questions this research experimentally investigates behavioral dynamics in continuous-time strategic environments. We find that adaptive models provide remarkably powerful tools for identifying which strategic environments exhibit convergence to equilibrium and for characterizing disequilibrium dynamics in non-convergent strategic environments