2026
2026Welfare and Cost Aggregation for Multi-Agent Control: When to Choose Which Social Cost Function, and Why?I. Shilov, E. Elokda, S. Hall, H. H. Nax, S. BolognaniIEEE Open Journal of Control Systems, 2026Which social cost function a multi-agent controller should minimise follows from how far the agents' costs can be compared. Choosing the welfare function
welfarist controlDOIarXiv2026Invariant Price of Anarchy and Multiplicative SmoothnessI. Shilov, H. H. Nax, S. BolognaniIEEE Conference on Decision and Control (CDC), 2026Price-of-anarchy bounds that do not change when one agent's costs are rescaled, from a product-form smoothness condition matched to Nash welfare. Price of anarchy
welfarist controlarXivCompanion site2026Invariant Price of Anarchy: a Metric for Welfarist Traffic ControlI. Shilov, M. He, H. H. Nax, E. Frazzoli, G. Zardini, S. BolognaniIFAC World Congress, 2026On the Zürich road network, the same toll can look efficient or wasteful depending on what one assumes about comparing travellers' costs. Price of anarchy
welfarist control, City of ZüricharXiv2026Comparability for Recommendation Model Evaluation and Selection from a Multi-stakeholder PerspectiveS. Ionescu, I. Shilov, F. DörflerACM Conference on Recommender Systems (RecSys), 2026, pp. 664–669Evaluating a recommender for users, providers and the platform at once, with Nash welfare when the stakeholders' benefits cannot be compared. Choosing the welfare function
welfarist controlDOIOpen copy2026A Welfarist Perspective on Fair Generation CurtailmentJ. G. Matt, I. Shilov, S. BolognaniIEEE PowerUp, 2026Existing curtailment schemes are the Kalai–Smorodinsky rule with different reference points; the testbed is a six-bus feeder in Walenstadt. Fair curtailment
welfarist control, WalenstadtarXivCompanion site2026Welfarist Control Design: How to Fulfill the Societal Mandate in Multi-Agent Control?S. Hall, K. Zhang, I. Shilov, H. H. Nax, S. BolognaniSubmitted to IEEE Control Systems MagazineA tutorial on designing controllers that share road space, grid capacity or user attention in line with a societal mandate. Choosing the welfare function
welfarist controlarXiv2026Fair With Respect to Whose Utility? Consistency of Welfare Proxies in Welfarist ControlI. Shilov, S. Bolognani, et al.In preparation
Choosing the welfare function
welfarist control2026Invariant Price of Anarchy and Multiplicative Smoothness (journal version)I. Shilov, H. H. Nax, S. BolognaniIn preparation for IEEE Transactions on Automatic Control
Price of anarchy
welfarist control2024
2024Forecast Trading as a Means to Reach Social Optimum on a Peer-to-Peer MarketI. Shilov, H. Le Cadre, A. Bušić, A. Sanjab, P. PinsonNETGCOOP 2024, Lecture Notes in Computer Science 15185, SpringerWhen prosumers can buy forecasts of renewable output, the peer-to-peer market can reach the social optimum. Uncertainty: risk and forecasts
peer-to-peer marketsDOI2023
2023Game-Theoretic Approaches for Peer-to-Peer Energy TradingI. ShilovPhD thesis, École Normale Supérieure (PSL), with Inria Paris and VITO peer-to-peer marketsHAL2023Towards Forecast Markets for Enhanced Peer-to-Peer Electricity TradingI. Shilov, H. Le Cadre, A. Bušić, A. Sanjab, P. PinsonIEEE SmartGridComm 2023, Glasgow Uncertainty: risk and forecasts
peer-to-peer marketsDOI2022
2022Uncertainty: risk and forecasts
peer-to-peer marketsHAL2021
2021Market equilibria on the grid
peer-to-peer marketsIEEE Xplore2021Privacy
peer-to-peer marketsarXiv2020
2020Uncertainty: risk and forecasts
peer-to-peer marketsarXivChoosing the welfare function
Price of anarchy
Fair curtailment
Market equilibria on the grid
Privacy
Uncertainty: risk and forecasts
13 papers, preprints and the thesis, and 2 in preparation.