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Controlling evolutionary dynamics of networked autonomous agents

Total Cost €


EC-Contrib. €






Project "CORNEA" data sheet

The following table provides information about the project.


Organization address
address: Broerstraat 5
postcode: 9712CP

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Netherlands [NL]
 Total cost 1˙998˙933 €
 EC max contribution 1˙998˙933 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2017-COG
 Funding Scheme ERC-COG
 Starting year 2018
 Duration (year-month-day) from 2018-05-01   to  2023-04-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Large-scale technological, biological, economic, and social complex systems act as complex networks of interacting autonomous agents. Large numbers of interacting agents making self-interested decisions can result in highly complex, sometimes surprising, and often suboptimal, collective behaviors. Empowered by recent breakthroughs in data-driven cognitive learning technologies, networked agents collectively give rise to evolutionary dynamics that cannot be easily modeled, analysed and/or controlled using current systems and control theory. Consequently, there is an urgent need to develop new theoretical foundations to tackle the emerging challenging control problems associated with evolutionary dynamics for networked autonomous agents.

The aim of this project is to develop a rigorous theory for the control of evolutionary dynamics so that interacting autonomous agents can be guided to solve group tasks through the pursuit of individual goals in an evolutionary dynamical process. The theory will then be tested, validated and improved against experimental results using robotic fish.

To achieve the aim, I will: (1) develop a general formulation for stochastic evolutionary dynamics with control inputs, enabling the study on controllability and stabilizability for evolutionary processes; (2) introduce stochastic control Lyapunov functions to design control laws; (3) construct new classes of conditional strategies that may propagate controlled actions effectively from focal agents in multiple time scales; and (4) validate experimentally on tasks with unknown difficulties that require a group of robotic fish to evolve and adapt.

The project will result in a major advance from the conventional usage of evolutionary game theory with the systematic design to actively control evolutionary outcomes. The combination of theory with experimentation and the multi-disciplinary nature of the approach will lead to new applications of autonomous robotic systems.


year authors and title journal last update
List of publications.
2018 Yu Kawano, Ming Cao
Differential Privacy and Qualitative Privacy Analysis for Nonlinear Dynamical Systems
published pages: 52-57, ISSN: 2405-8963, DOI: 10.1016/j.ifacol.2018.12.010
IFAC-PapersOnLine 51/23 2020-03-23
2019 James Riehl, Pouria Ramazi, Ming Cao
Incentive-Based Control of Asynchronous Best-Response Dynamics on Binary Decision Networks
published pages: 727-736, ISSN: 2325-5870, DOI: 10.1109/tcns.2018.2873166
IEEE Transactions on Control of Network Systems 6/2 2020-03-23
2019 Mengbin Ye, Yuzhen Qin, Alain Govaert, Brian D.O. Anderson, Ming Cao
An influence network model to study discrepancies in expressed and private opinions
published pages: 371-381, ISSN: 0005-1098, DOI: 10.1016/j.automatica.2019.05.059
Automatica 107 2020-03-23
2019 Yu Kawano, Ming Cao
Structural Accessibility and Its Applications to Complex Networks Governed by Nonlinear Balance Equations
published pages: 4607-4614, ISSN: 0018-9286, DOI: 10.1109/tac.2019.2901822
IEEE Transactions on Automatic Control 64/11 2020-03-23
2019 Cenedese, Carlo; Belgioioso, Giuseppe; Grammatico, Sergio; Cao, Ming
An asynchronous, forward-backward, distributed generalized nash equilibrium seeking algorithm
published pages: , ISSN: , DOI: 10.13140/rg.2.2.27907.35364
2019 18th European Control Conference, ECC 2019, 3508 - 3513 5 2020-03-23
2019 Brian D. O. Anderson, Mengbin Ye
Recent Advances in the Modelling and Analysis of Opinion Dynamics on Influence Networks
published pages: 129-149, ISSN: 1476-8186, DOI: 10.1007/s11633-019-1169-8
International Journal of Automation and Computing 16/2 2020-03-23
2019 Mengbin Ye, Ji Liu, Lili Wang, Brian D. O. Anderson, Ming Cao
Consensus and Disagreement of Heterogeneous Belief Systems in Influence Networks
published pages: 1-1, ISSN: 0018-9286, DOI: 10.1109/tac.2019.2961998
IEEE Transactions on Automatic Control 2020-03-23
2019 Yu Kawano, Lulu Gong, Brian D. O. Anderson, Ming Cao
Evolutionary Dynamics of Two Communities Under Environmental Feedback
published pages: 254-259, ISSN: 2475-1456, DOI: 10.1109/lcsys.2018.2866775
IEEE Control Systems Letters 3/2 2020-03-23
2019 Zhongqi Sun, Vahab Rostampour, Ming Cao
Self-Triggered Stochastic MPC for Linear Systems With Disturbances
published pages: 787-792, ISSN: 2475-1456, DOI: 10.1109/lcsys.2019.2918763
IEEE Control Systems Letters 3/4 2020-03-23
2018 James R. Riehl, Ming Cao
A Centrality-Based Security Game for Multihop Networks
published pages: 1507-1516, ISSN: 2325-5870, DOI: 10.1109/tcns.2017.2728202
IEEE Transactions on Control of Network Systems 5/4 2020-03-23
2018 Satoshi Kawamura, Kai Cai, Mengbin Ye, Zhiyun Lin
Tight bound on parameter of surplus-based averaging algorithm over balanced digraphs
published pages: 1-8, ISSN: 0020-7179, DOI: 10.1080/00207179.2018.1535200
International Journal of Control 2020-03-23

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