Annealing schedule from population dynamics
Stefan Bornholdt
Abstract
We introduce a dynamical annealing schedule for population-based optimization algorithms with mutation. On the basis of a statistical mechanics formulation of the population dynamics, the mutation rate adapts to a value maximizing expected rewards at each time step. Thereby, the mutation rate is eliminated as a free parameter from the algorithm.
Create a lesson
Related papers
Long-time Dynamics of Many-body Open Quantum Systems using Quantum Generating Functions
Katha Ganguly, Dario Poletti, Bijay Kumar Agarwalla
Localization Delocalization Transition in Diffusion with Adaptive Resetting
Tommer D. Keidar, Shlomi Reuveni
Quenched activity induces nonuniversal scaling in nonreciprocal XY Models and surfaces
Sudip Mukherjee, Abhik Basu
Brownian yet non-Gaussian diffusion through equilibrium nonlinear friction
Jakob Mihatsch, Andreas M. Menzel
When dissipative steady states admit thermodynamic occupation laws
Tetsu Ichitsubo
Fluctuation--response relations from an emergent Z2 symmetry in the rotating stochastic Landau model
Dhruv Kush, Nicki Mullins, Mauricio Hippert et al.