Design and Simulation of Cooperative Hybrid Systems (HYBRIDA)

Type: National Project Project

Duration: from 2021 Jan 01 to 2023 Dec 31

Financed by: FCT

Prime Contractor: R - INESC-ID Lisboa (Other) - Lisboa, Portugal

This project aims to develop and apply new multiagent learning models — based on social and individual-based learning — to understand how human cooperative collective action may resist the threat of free-riding, in the context of stochastic time-evolving and time-delayed sequential dilemmas. We will address reputation-based dynamics, inequality of roles, intergenerational conflicts, incipient forms of democracy, and the liability of key players in political networks. We shall also address the formation and impact of institutions adopting different forms of incentives. Agent-based models, grounded on game theory, network science and population dynamics, combined with behavioral data from lab experiments, will allow us to perform controlled simulations of dilemmas coupled to evolving common-pool resources, to unveil and rank the importance and effect of each ingredient in collective success.


  • R - INESC-ID Lisboa (Other) - Lisboa, Portugal
  • Universidade do Minho (University) - Braga, Portugal

Principal Investigators