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Raffaele Pesenti

Publications and source records attributed to Raffaele Pesenti.

6 recordsLinked to original sources

An agent-based decentralized threshold policy finding the constrained shortest paths

We consider a problem where autonomous agents enter a dynamic and unknown environment described by a network of weighted arcs. These agents move within the network from node to node according to a decentralized policy using only local information, with the goal of finding a path to an unknown sink node to leave the network. This policy makes each agent move to some adjacent node or stop at the current node. The transition along an arc is allowed or denied based on a threshold mechanism that takes into account the number of agents already accumulated in the arc's end nodes and the arc's weight. We show that this policy ensures path-length optimality in the sense that, in a finite time, all new agents entering the network reach the closer sinks by the shortest paths. Our approach is later extended to support constraints on the paths that agents can follow.

math.OC

Lightning optimizes: a threshold mechanism ensures minimum-path flow

A well-known property of linear resistive electrical networks is that the current distribution minimizes the total dissipated energy. When the circuit includes resistors with nonlinear monotonic characteristic, the current distribution minimizes in general a different functional. We show that, if the nonlinear characteristic is a threshold-like function and the energy generator is concentrated in a single point, as in the case of lightning or dielectric discharge, then the current flow is concentrated along a single path, which is a minimum path to the ground with respect to the threshold. We also propose a dynamic model that explains and qualitatively reproduces the lightning transient behaviour: initial generation of several plasma branches and subsequent dismissal of all branches but the one reaching the ground first, which is the optimal one.

math.OC

Origin-to-destination network flow with path preferences and velocity controls: a mean field game-like approach

In this paper we consider a mean field approach to modeling the agents flow over a transportation network. In particular, beside a standard framework of mean field games, with controlled dynamics by the agents and costs mass-distribution dependent, we also consider a path preferences dynamics obtained as a generalization of the so-called noisy best response dynamics. Such a preferences dynamics says the agents choose their path having access to global information about the network congestion state and based on the observation of the decision of the agents that have preceded. We prove the existence of a mean field equilibrium obtained as a fixed point of a map over a suitable set of time-varying mass-distributions, defined edge by edge in the network. We also address the case where the admissible set of controls is suitably bounded depending on the mass-distribution on the edge itself.

math.OC

A mean field approach to model flows of agents with path preferences over a network

In this paper, we address the problem of modeling the traffic flow of a heritage city whose streets are represented by a network. We consider a mean field approach where the standard forward backward system of equations is also intertwined with a path preferences dynamics. The path preferences are influenced by the congestion status on the whole network as well as the possible hassle of being forced to run during the tour. We prove the existence of a mean field equilibrium as a fixed point, over a suitable set of time-varying distributions, of a map obtained as a limit of a sequence of approximating functions. Then, a bi-level optimization problem is formulated for an external controller who aims to induce a specific mean field equilibrium.

math.OC

Optimal control of the mean field equilibrium for a pedestrian tourists' flow model

Art heritage cities are popular tourist destinations but for many of them overcrowding is becoming an issue. In this paper, we address the problem of modeling and analytically studying the flow of tourists along the narrow alleys of the historic center of a heritage city. We initially present a mean field game model, where both continuous and switching decisional variables are introduced to respectively describe the position of a tourist and the point of interest that he/she may visit. We prove the existence of a mean field equilibrium. A mean field equilibrium is Nash-type equilibrium in the case of infinitely many players. Then, we study an optimization problem for an external controller who aims to induce a suitable mean field equilibrium.

math.OC

Consensus for switched networks with unknown but bounded disturbances

We consider stationary consensus protocols for networks of dynamic agents with switching topologies. The measure of the neighbors' state is affected by Unknown But Bounded disturbances. Here the main contribution is the formulation and solution of what we call the $ε$-consensus problem, where the states are required to converge in a tube of ray $ε$ asymptotically or in finite time.

math.OC