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Matjaz Perc

Researcher at University of Maribor

Publications -  148
Citations -  15496

Matjaz Perc is an academic researcher from University of Maribor. The author has contributed to research in topics: Public goods game & Population. The author has an hindex of 57, co-authored 148 publications receiving 12886 citations. Previous affiliations of Matjaz Perc include King Abdulaziz University & China Medical University (Taiwan).

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Stability and Stabilization in Probability of Probabilistic Boolean Networks

TL;DR: To simulate more realistic cellular systems, the probability of stability/stabilization is not required to be a strict one, and some necessary and sufficient conditions are proposed via the semitensor product of matrices.
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Stability of subsystem solutions in agent-based models

TL;DR: It is shown that a satisfactory answer can only be obtained by means of a complete stability analysis of subsystem solutions, and it is crucial that the competing subsystem solutions are characterised by a proper composition and spatiotemporal structure before the competition starts.
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Evolutionary dynamics in the public goods games with switching between punishment and exclusion.

TL;DR: In this article, the authors proposed two different switching strategies, namely, peer switching that is based on peer punishment and peer exclusion, and pool switching based on pool punishment and pool exclusion.
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Evolution of public cooperation in a monitored society with implicated punishment and within-group enforcement

TL;DR: In this article, the authors show that the introduction of monitoring and implicated punishment is indeed effective, as it transforms the public goods game to a coordination game, thus rendering cooperation viable in infinite and finite well-mixed populations.
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Evolutionary dynamics of cooperation in neutral populations

TL;DR: In this paper, the authors use the prisoner's dilemma game as the mathematical model and show that considering several populations simultaneously give rise to fascinating spatiotemporal dynamics and pattern formation, and they reveal that considering the simultaneous presence of different populations significantly expands the complexity of evolutionary dynamics in structured populations, and it allow us to understand the stability of cooperation under adverse conditions that could never be bridged by network reciprocity alone.