121 citations · 244 across the 13 of their papers we have counts for
13 papers
Auditing Algorithmic Collusion from Strategy Graphs
Nicolas Eschenbaum, Janusz M. Meylahn
Detecting algorithmic collusion is challenging because regulators often have limited access to firms' algorithms, training data, and market information. We study an intermediate-in…
Equilibrium stability as a driver of cooperation among Q-learners
Janusz M. Meylahn, Maximilian Schäfer
Algorithmic collusion among pricing algorithms has raised concerns about sustained supra-competitive prices and their implications for social welfare. Existing work has largely foc…
Beyond the Independence Assumption: Finite-Sample Guarantees for Deep Q-Learning under -Mixing
Leon Halgryn, Sophie Langer, Janusz M. Meylahn +1
Finite-sample analyses of deep Q-learning typically treat replayed data as independent, even though it is sampled from temporally dependent state-action trajectories. We study the…
How social reinforcement learning can lead to metastable polarisation and the voter model
Benedikt V. Meylahn, Janusz M. Meylahn
Previous explanations for the persistence of polarization of opinions have typically included modelling assumptions that predispose the possibility of polarization (i.e., assumptio…
Risk aversion can promote cooperation
Jay Armas, Wout Merbis, Janusz Meylahn +2
Cooperative dynamics are central to our understanding of many phenomena in living and complex systems. However, we lack a universal mechanism to explain the emergence of cooperatio…
Intrinsic fluctuations of reinforcement learning promote cooperation
Wolfram Barfuss, Janusz Meylahn
In this work, we ask for and answer what makes classical temporal-difference reinforcement learning with epsilon-greedy strategies cooperative. Cooperating in social dilemma situat…
Limiting dynamics for Q-learning with memory one in symmetric two-player, two-action games
Janusz M Meylahn, Lars Janssen
We develop a method based on computer algebra systems to represent the mutual pure strategy best-response dynamics of symmetric two-player, two-action repeated games played by play…
Two-community noisy Kuramoto model with general interaction strengths: Part II
Stefan Achterhof, Janusz M Meylahn
We generalize the study of the noisy Kuramoto model, considered on a network of two interacting communities, to the case where the interaction strengths within and across communiti…
Two-community noisy Kuramoto model with general interaction strengths: Part I
Stefan Achterhof, Janusz M. Meylahn
We generalize the study of the noisy Kuramoto model, considered on a network of two interacting communities, to the case where the interaction strengths within and across communiti…
Two-community noisy Kuramoto model
J. M. Meylahn
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…
Properties of additive functionals of Brownian motion with resetting
Frank den Hollander, Satya N. Majumdar, Janusz M. Meylahn +1
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 t…
Synchronization of phase oscillators on the hierarchical lattice
Diego Garlaschelli, Frank den Hollander, Janusz Meylahn +1
Synchronization of neurons forming a network with a hierarchical structure is essential for the brain to be able to function optimally. In this paper we study synchronization of ph…
Large deviations for Markov processes with resetting
Janusz M. Meylahn, Sanjib Sabhapandit, Hugo Touchette
Markov processes restarted or reset at random times to a fixed state or region in space have been actively studied recently in connection with random searches, foraging, and popula…