Theo dõi
Janusz Meylahn
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Năm
Large deviations for Markov processes with resetting
JM Meylahn, S Sabhapandit, H Touchette
Physical Review E 92 (6), 062148, 2015
1142015
Properties of additive functionals of Brownian motion with resetting
F Den Hollander, SN Majumdar, JM Meylahn, H Touchette
Journal of Physics A: Mathematical and Theoretical 52 (17), 175001, 2019
672019
Learning to collude in a pricing duopoly
JM Meylahn, A V. den Boer
Manufacturing & Service Operations Management 24 (5), 2577-2594, 2022
392022
Artificial Collusion: Examining Supracompetitive Pricing by Q-Learning Algorithms
AV den Boer, JM Meylahn, MP Schinkel
Amsterdam Law School Research Paper, 2022
352022
Intrinsic fluctuations of reinforcement learning promote cooperation
W Barfuss, JM Meylahn
Scientific Reports 13 (1), 1309, 2023
272023
Limiting dynamics for Q-learning with memory one in symmetric two-player, two-action games
JM Meylahn, L Janssen
Complexity 2022, 2022
222022
Two-Community Noisy Kuramoto Model Suggests Mechanism for Splitting in the Suprachiasmatic Nucleus
JHT Rohling, JM Meylahn
Journal of Biological Rhythms 35 (2), 158-166, 2020
132020
Two-community noisy Kuramoto model
JM Meylahn
Nonlinearity 33, 1847-1880, 2020
132020
Synchronization of phase oscillators on the hierarchical lattice
D Garlaschelli, F den Hollander, JM Meylahn, B Zeegers
Journal of Statistical Physics 174 (1), 188-218, 2019
92019
Quantifying the likelihood of learning collusive strategy equilibria
JM Meylahn
Available at SSRN 4589989, 2023
7*2023
Algorithmic Collusion: Where Are We and Where Should We Be Going?
I Abada, JE Harrington Jr, X Lambin, JM Meylahn
Available at SSRN 4891033, 2024
62024
Biofilament interacting with molecular motors
JM Meylahn
Stellenbosch: Stellenbosch University, 2015
62015
A (mathematical) definition of algorithmic collusion
AV den Boer, JM Meylahn
Available at SSRN 5012923, 2024
52024
Does an intermediate price facilitate algorithmic collusion?
JM Meylahn
Available at SSRN 4594415, 2024
52024
Reduced Plasticity in Coupling Strength in the Aging SCN Clock as Revealed by Kuramoto Modeling
AW van Beurden, JM Meylahn, S Achterhof, R Buijink, A Olde Engberink, ...
Journal of Biological Rhythms 38 (5), 461-475, 2023
52023
Two-community noisy Kuramoto model with general interaction strengths. II
S Achterhof, JM Meylahn
Chaos: An Interdisciplinary Journal of Nonlinear Science 31 (3), 2021
42021
Risk aversion can promote cooperation
J Armas, W Merbis, J Meylahn, SR Rad, MJ del Razo
Journal of Physics: Complexity 6 (1), 015010, 2025
2*2025
How social reinforcement learning can lead to metastable polarisation and the voter model
BV Meylahn, JM Meylahn
PloS one 19 (12), e0313951, 2024
12024
Can Decentralized Q-learning learn to collude?
JM Meylahn
Seventeenth European Workshop on Reinforcement Learning, 2024
2024
Two-community noisy Kuramoto model with general interaction strengths. I
S Achterhof, J Meylahn
Chaos: An Interdisciplinary Journal of Nonlinear Science 31 (3), 033115, 2021
2021
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