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Discrete time markovian agents interacting through a potential

Amarjit Budhiraja, Pierre Del Moral, Sylvain Rubenthaler (2013)

ESAIM: Probability and Statistics

A discrete time stochastic model for a multiagent system given in terms of a large collection of interacting Markov chains is studied. The evolution of the interacting particles is described through a time inhomogeneous transition probability kernel that depends on the ‘gradient’ of the potential field. The particles, in turn, dynamically modify the potential field through their cumulative input. Interacting Markov processes of the above form have been suggested as models for active biological transport...

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