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- John Realpe-Gomez, Bartosz Szczesny, Luca Dall'Asta, Tobias Galla
- ArXiv
- 2011

Evolutionary dynamics in finite populations is known to fixate eventually in the absence of mutation. We here show that a similar phenomenon can be found in stochastic game dynamical batch learning, and investigate fixation in learning processes in a simple 2 × 2 game, for two-player games with cyclic interaction, and in the context of the best-shot network… (More)

Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). Based on the cavity method of statistical mechanics, we introduce… (More)

In a graphical game agents play with their neighbors on a graph to achieve an appropriate state of equilibrium. Here relevant problems are characterizing the equilibrium set and discovering efficient algorithms to find such an equilibrium (solution). We consider a representation of games that extends over graphical games to deal conveniently with both local… (More)

- John Realpe-Gomez, Tobias Galla, Alan J McKane
- Physical review. E, Statistical, nonlinear, and…
- 2012

We explore a class of hybrid (piecewise deterministic) systems characterized by a large number of individuals inhabiting an environment whose state is described by a set of continuous variables. We use analytical and numerical methods from nonequilibrium statistical mechanics to study the influence that intrinsic noise has on the qualitative behavior of the… (More)

The scarcity of water characterising drylands forces vegetation to adopt appropriate survival strategies. Some of these generate water-vegetation feedback mechanisms that can lead to spatial self-organisation of vegetation, as it has been shown with models representing plants by a density of biomass, varying continuously in time and space. However, although… (More)

Mainstream machine learning techniques such as deep learning and probabilistic programming rely heavily on sampling from generally intractable probability distributions. There is increasing interest in the potential advantages of using quantum computing technologies as sampling engines to speedup these tasks. However, some pressing challenges in… (More)

We study the behaviour of charge oscillations in Superconducting Cooper Pair Boxes weakly interacting with an environment. We found that, due to the noise and dissi-pation induced by the environment, the stability properties of these nanodevices differ according to whether the charge oscillations are interpreted as an effect of macroscopic quantum… (More)

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