arXiv subjects

Pietro Terna

Publications and source records attributed to Pietro Terna.

5 recordsLinked to original sources

arXiv2026

A Note on Reinforcement Learning to Develop Self-defined Agents' Behavior

The key point in this note is the self-development of simple behavior strategies, consistently with the bounded rationality hypothesis. Our artificial agents adopt learning techniques, mainly unsupervised, to achieve internal consistency in their behavior, with unexpected results. Those results can be considered mainly as the effects of the observer interpretation. The first technique in use has the name Cross Targets: to train the learning agent we use data crossed between the guesses about the action to be done and the guesses about the following results. An application of the CT "blind" strategy development is then presented: random walkers solve a node classification problem on a graph, after having learnt how to remain in homogeneous regions.

cs.SI↗

arXiv2025

How many outbreaks before an epidemic?

In this work, we study the finite-population behaviour of the Reed-Frost epidemic model. Our analysis relies on the exact expression for the final epidemic size, replaced by Monte Carlo simulations in cases where the exact formula becomes numerically unstable. When the initial reproduction number is greater than a critical threshold, the distribution of the final size becomes bimodal. We therefore define the probabilities of small and large outbreaks, providing an intuitive answer to the question posed in the title through simple arguments based on the geometric distribution. Finally, an agent-based simulation confirms that the Reed-Frost model offers a good approximation in the case of the COVID-19 outbreak.

q-bio.PE↗

arXiv2024

Breaking open the black box of the production function: an agent-based model accounting for time in production processes

Traditional notions of production function do not consider the time dimension, appearing thus timeless and instantaneous. We propose an agent-based model accounting for the whole production side of the economy to unfold the production process from its very beginning, when firms receive production orders, to the delivery of the products to the market. In the model we analyze with a high-degree of details how heterogeneous firms, having labor and capital as productive factors, behave along all the realization processes of their outputs. The main focus covers: i) the heterogeneous duration of firms' production processes, ii) the adaptive strategies they implement to adjust their choices, and iii) the possible failures which may occur due to the duration of the production. Our agent-based model is a controlled experiment: we use a virtual central planner mechanism, which acts as the demand side of the economy, to observe which firm individual behaviors and aggregate macroeconomic outcomes emerge as a reply to its different behaviors in a ceteris paribus environment. Our applied goal, then, is to discuss the role of industrial policy by modeling production processes in detail.

econ.GN↗

arXiv2021

An Agent-Based Model of COVID-19 Diffusion to Plan and Evaluate Intervention Policies

A model of interacting agents, following plausible behavioral rules into a world where the Covid-19 epidemic is affecting the actions of everyone. The model works with (i) infected agents categorized as symptomatic or asymptomatic and (ii) the places of contagion specified in a detailed way. The infection transmission is related to three factors: the characteristics of both the infected person and the susceptible one, plus those of the space in which contact occurs. The model includes the structural data of Piedmont, an Italian region, but we can easily calibrate it for other areas. The micro-based structure of the model allows factual, counterfactual, and conditional simulations to investigate both the spontaneous or controlled development of the epidemic. The model is generative of complex epidemic dynamics emerging from the consequences of agents' actions and interactions, with high variability in outcomes and stunning realistic reproduction of the successive contagion waves in the reference region. There is also an inverse generative side of the model, coming from the idea of using genetic algorithms to construct a meta-agent to optimize the vaccine distribution. This agent takes into account groups' characteristics -- by age, fragility, work conditions -- to minimize the number of symptomatic people.

cs.MA↗

arXiv2020

Active particles methods towards modeling in science and society

This paper is a first step to chase the ambitious objective of developing a mathmatical theory of living systems. The contents refer modeling large systems of interacting living entities with the aim of describing their collective behaviors by differential models. The contents is in three parts. Firstly, we derive the mathematical method; subsequently, we show how the method can be applied in a number of case studies related to well defined living systems and finally, we look ahead to research perspectives focusing both on mathematical methods and further applications.

cond-mat.soft↗