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Last update: September 4, 2019

Carlo Piccardi

DEIB - Dipartimento di Elettronica, Informazione e Bioingegneria
Politecnico di Milano
Piazza Leonardo da Vinci 32
20133 Milano, Italy

tel (++39) 02 2399 3566
fax (++39) 02 2399 3412
e-mail carlo.piccardi@polimi.it
web page http://home.deib.polimi.it/piccardi/

Click here for details on recent research activities (some with codes and data available).

Check the list of my publications on peer reviewed journals (or visit my Google Scholar page).

    [research highlights]
A. Mechiche-Alami, C. Piccardi, K.A. Nicholas, J.W. Seaquist, Transnational land acquisitions beyond the food and financial crises, Environmental Research Letters, 14, 084021, 2019. [doi]

Large-scale land acquisitions (LSLA) in resource-rich countries came to global attention after the food and financial crises of 2008. Previous research has assessed themagnitude of these land investments in terms of land areas acquired. In this study,we analyze the trends in the evolution of LSLAby framing the latter as virtual land trade networkwith land transactions occurring between 2000 and 2015, in order to shed light on the development and evolution of this system. Based on an index we introduce to represent both the number of countries and size of deals,we discover threemain phases of trade activity: a steady increase from2000 until 2007 (Phase 1) followed by a peak coincidingwith the food and financial crises between 2008 and 2010 (Phase 2) and concluded by a decline from2011 to 2015 (Phase 3).We identify 73 countries that remained active in land trading during all three phases and forma core of land traders much larger than previously thought. Using network analysismethods, we group countries with similar trade patterns into categories of competitive, preferential, diversified, and occasional importers or exporters. Finally, in exploring the changes in investors and their interests in land throughout the phases, we attribute the evolution of LSLAto the different stages in the globalization and financialization of different industries. By showing that land investments seemfully integrated as investment strategies across industries we argue for the urgency of better regulation of LSLAso that they also benefit local populationswithout damaging the environment regardless of their primary purpose.
F. Riva, E. Colombo, C. Piccardi, Towards modelling diffusion mechanisms for sustainable off-grid electricity planning, Energy for Sustainable Development, 52, 11-25, 2019. [doi]

The electrification-based literature reports a limited knowledge about the mechanisms of evolution of electricity demand in off-grid settings, especially in remote contexts of developing countries, due to the lack of robust and appropriate modelling frameworks. Such lack of understanding and modelling endeavour contributes to an inefficient allocation of resources for electrification projects and inappropriate off-grid sizing processes. As a first step towards the development of a more appropriate electricity demand model, we present a comparative study of two approaches for modelling different diffusion mechanisms of electricity connections: system-dynamics and agent-based models. The latter includes the modelling of social network archetypes in the simulation of diffusion processes. We model different scenarios of diffusion and we use them for evaluating the impact on the sizing process of an off-grid hydroelectric system. The results suggest that the structure of the social network can represent a crucial parameter that can impact on timing needed to complete the diffusion of electricity access – from few months to even >10 years. This affects the sizing process and the long-term sustainability of the power system, leading to variation of the hydroelectric capacity and the battery size up to around 55% and 100%, respectively. Our results indicate that the agent-based approach allows a more diversified representation of diffusion processes, but the limitations and scarcity of data can be an obstacle to their prompt application for energy application in unelectrified areas. On the contrary, system-dynamics can represent a more appropriate method since it requires less quantitative data and it provides a more structural and holistic modelling framework for conceptualising and formulating in a the determinants and complexities affecting the evolution of electricity demand in unelectrified areas.
F. Dercole, F. Della Rossa, C. Piccardi, Direct reciprocity and model-predictive rationality explain network reciprocity over social ties, Scientific Reports, 9, 5367, 2019. [doi]

Since M. A. Nowak & R. May’s (1992) influential paper, limiting each agent’s interactions to a few neighbors in a network of contacts has been proposed as the simplest mechanism to support the evolution of cooperation in biological and socio-economic systems. The network allows cooperative agents to self-assort into clusters, within which they reciprocate cooperation. This (induced) network reciprocity has been observed in several theoreticalmodels and shown to predict the fixation of cooperation under a simple rule: the benefit produced by an act of cooperation must outweigh the cost of cooperating with all neighbors. However, the experimental evidence among humans is controversial: though the rule seems to be confirmed, the underlying modeling assumptions are not. Specifically, models assume that agents update their strategies by imitating better performing neighbors, even though imitation lacks rationality when interactions are far from all-to-all. Indeed, imitation did not emerge in experiments. What did emerge is that humans are conditioned by their own mood and that, when in a cooperative mood, they reciprocate cooperation. To help resolve the controversy, we design a model in which we rationally confront the two main behaviors emerging from experiments—reciprocal cooperation and unconditional defection—in a networked prisoner’s dilemma. Rationality is introduced by means of a predictive rule for strategy update and is bounded by the assumed model society. We show that both reciprocity and a multi-step predictive horizon are necessary to stabilize cooperation, and sufficient for its fixation, provided the game benefit-to-cost ratio is larger than a measure of network connectivity. We hence rediscover the rule of network reciprocity, underpinned however by a different evolutionary mechanism.


I am Full Professor at Politecnico di Milano. My teaching activity is in the area of complex systems and networks, dynamical systems and automatic control, both to undergraduate and graduate students of the Politecnico schools of engineering. I also teach in the PhD program of my Department (DEIB), mostly in the area of complex systems.

My research interests are focused on several topics concerning complex systems. Some recent areas of research are:

  • Structural properties of networks, with applications in economics, finance, and social sciences;
  • Spreading processes on complex networks;
  • Synchronization of networks of dynamical systems;
  • Reduced models for nonlinear systems, and their use for solving control and parameter estimation problems; 
  • Application of optimal control techniques to nonlinear systems; 
  • The use of numerical methods for bifurcation analysis of nonlinear systems, including continuation methods and harmonic-balance techniques; 
  • The analysis of structural properties of cooperative systems.