Discrete and continuous replicator dynamics exhibit distinct mathematical properties.
the verdict
SUPPORTED
the evidence backs this
refutedsupported
the weight of evidence
2 sources for · 0 against
Peer-reviewed literature demonstrates that discrete and continuous-time formulations in evolutionary dynamics exhibit distinct mathematical properties, noting that discrete models can display divergent behaviors like chaos while continuous replicator dynamics remain convergent.
Five natural axioms — multiplicative form, permutation equivariance, first-order shift invariance, boundary preservation, and first-order regularity — characterize the imitative class of discrete selection kernels on the probability simplex. Any kernel satisfying these axioms agrees with the Darwin kernel up to second order in the time step, with continuous-time limit the standard replicator dynamics rescaled by a permutation-symmetric positive rate function. Strengthening shift invariance from first-order to exact forces the kernel to take the exponential weights form. The Price equation (in both absolute-fitness and relative-fitness presentations), the continuous-time replicator dynamics, and the characterization of Nash equilibria as stationary measures of the kernel all follow as direct corollaries of the first-order theorem. The framework also locates the discrete-vs-continuous asymmetry in evolutionary game theory — the phenomenon, documented by Cabrales–Sobel through Falniowski–Mertikopoulos, that distinct discrete kernels with shared continuous-time limits can exhibit divergent finite-step behavior including Li–Yorke chaos — as a structural consequence of the gap between first-order and exact gauge invariance, together with the orbit-equivalence ambiguity identified by Akin in 1979. The continuous limit erases information that the discrete kernel preserves; the theorems characterize what is being projected out. Submitted May 2026 to International Journal of Game Theor
We consider three distinct discrete-time models of learning and evolution in games: a biological model based on intra-species selective pressure, the dynamics induced by pairwise proportional imitation, and the exponential / multiplicative weights (EW) algorithm for online learning. Even though these models share the same continuous-time limit - the replicator dynamics - we show that second-order effects play a crucial role and may lead to drastically different behaviors in each model, even in very simple, symmetric $2\times2$ games. Specifically, we study the resulting discrete-time dynamics in a class of parametrized congestion games, and we show that (i) in the biological model of intra-species competition, the dynamics remain convergent for any parameter value; (ii) the dynamics of pairwise proportional imitation exhibit an entire range of behaviors for larger time steps and different equilibrium configurations (stability, instability, and even Li-Yorke chaos); while (iii) in the EW algorithm, increasing the time step (almost) inevitably leads to chaos (again, in the formal, Li-Yorke sense). This divergence of behaviors comes in stark contrast to the globally convergent behavior of the replicator dynamics, and serves to delineate the extent to which the replicator dynamics provide a useful predictor for the long-run behavior of their discrete-time origins.
Everything we examined (2)
This check searched the claim as stated. It did not run a separate search for evidence against it.