Intrinsic fluctuations of reinforcement learning promote cooperation

Autor: Wolfram Barfuss, Janusz M. Meylahn

Publikováno v: Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)

Abstract In this work, we ask for and answer what makes classical temporal-difference reinforcement learning with $$\epsilon$$ ϵ -greedy strategies cooperative. Cooperating in social dilemma situations is vital for animals, humans, and machines. Whi

Externí odkaz: https://doaj.org/article/e121f2b9f63c42998d299cc72545212c

Two-community noisy Kuramoto model

Autor: Janusz M Meylahn

Publikováno v: Nonlinearity. 33:1847-1880

We study the noisy Kuramoto model for two interacting communities of oscillators, where we allow the interaction in and between communities to be positive or negative (but not zero). We find that, in the thermodynamic limit where the size of the two

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cdec179e1c55476f4fba468fd68a9bfb
https://doi.org/10.1088/1361-6544/ab6814

Limiting dynamics for Q-learning with memory one in two-player, two-action games

Autor: Janusz M Meylahn

Publikováno v: SSRN Electronic Journal.

We develop a computational method to identify all pure strategy equilibrium points in the strategy space of the two-player, two-action repeated games played by Q-learners with one period memory. In order to approximate the dynamics of these Q-learner

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::114a0e1380992eded8da335fb6599e3c
https://doi.org/10.2139/ssrn.3895751

Learning to Collude in a Pricing Duopoly

Autor: Janusz M Meylahn, Arnoud V. den Boer

Publikováno v: SSRN Electronic Journal.

Problem definition: This paper addresses the question -- hotly debated in competition regulation circles -- whether or not self-learning algorithms can learn to collude instead of compete against each other, without violating existing competition law

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::034c3876cd1f237d872d178ed9c6487c
https://doi.org/10.2139/ssrn.3741385

Properties of additive functionals of Brownian motion with resetting

Autor: Satya N. Majumdar, Hugo Touchette, Janusz M Meylahn, Frank den Hollander

Publikováno v: Journal of Physics A: Mathematical and General (1975-2006)
Journal of Physics A: Mathematical and General (1975-2006), IOP Publishing, 2019, 52 (17), ⟨10.1088/1751-8121/ab0efd⟩
Journal of Physics A: Mathematical and Theoretical
Journal of Physics A: Mathematical and Theoretical, 52(17), 175001

We study the distribution of additive functionals of reset Brownian motion, a variation of normal Brownian motion in which the path is interrupted at a given rate and placed back to a given reset position. Our goal is two-fold: (1) For general functi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::37b36c2b85032e1d291917bcd128af74
https://hal.archives-ouvertes.fr/hal-02102127