Weak convergence conjecture for imitation dynamics

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Let A\mathbf{A} be a game matrix and let α\alpha be a learning rate. Suppose that the maximal set of IG(t)I_G(t) is constant for all t≥t0t\geq t_0. Let X∗\mathcal{X}^* denote the maximal set and let H(X∗)\mathcal{H}(\mathcal{X}^*) denote its convex hull. Weak convergence conjecture. There exists a rate α∗\alpha^* such that, if α<α∗\alpha<\alpha^*, the dynamics have an attracting fixed point of the imitation dynamics contained in H(X∗)\mathcal{H}(\mathcal{X}^*), and the dynamics converge to that fixed point. The conjecture concerns general convergence of imitation dynamics, which are not strict contractions; the source presents it as an open problem and gives examples of convergence but no proof of the claim.

References

Primary source

Christopher Griffin, Sarah Rajtmajer, Anna Squicciarini and Andrew Belmonte, “Consensus and Information Cascades in Game-Theoretic Imitation Dynamics with Static and Dynamic Network Topologies”, arXiv:1903.11429 (2019).

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