EPOS

EPOS, the Economic Planning and Optimized Selections, is a fully decentralized networked system designed for participatory multi-objective optimization forming a public good and supporting sharing economies. It performs collective decision-making among agents that autonomously generate a set of options from which they make a choice. Each agent is a human actor, a piece of software or a hybrid system of both that locally generates in a self-determined way a set of plan that define how some resources are allocated. For example, a plan may define the energy demand of a residential appliance in a future horizon or the availability of bicycles in the bicycle stations of a city. A set of several plans per agent represents alternative options, equivalent or not for the agent. This flexibility provides a degree of freedom in the overall aggregate allocation of resources in the system that results in a combinatorial explosion of possible trajectories of system-wise solutions: different combinations of local selections can lead to different desirable or undesirable global outcomes. EPOS is capable of steering such highly complex systems of combinatorial complexity to desirable outcomes by structuring agent interactions dynamic self-organized tree topologies and performing bottom-up collective decision-making using fitness functions designed to solve particular problems. for instance, preventing blackouts in smart grids by load-shifting or load-adjustment.
Both EPOS and I-EPOS can be applied to several application domains without changes in their core functionality. EPOS is primarily designed as a decentralized combinatorial optimization mechanism. I-EPOS, the Iterative EPOS system, adds decentralized back-propagation learning capabilities that improve system performance and the discovery of more efficient collective outcomes in an evolutionary fashion. Both EPOS and I-EPOS can be applied to several application domains without changes in their core functionality. Given its decentralization, scalability, local autonomy and collective decision-making, it can promote participation, fairness and sustainability in the sharing economies and application domains of energy, transportation, voting, Smart Cities and others.
Related Publications
- Evangelos Pournaras, Collective Learning: A 10-Year Odyssey to Human-centered Distributed Intelligence, IEEE International Conference on Autonomic Computing and Self-Organizing Systems-ACSOS-2020, Washington, USA, August 2020 © IEEE
- Farzam Fanitabasi, Evangelos Pournaras, Appliance-Level Flexible Scheduling for Socio-Technical Smart Grid Optimization, IEEE Access, 2020, IEEE
- Brionna Davis, Grace Jennings, Taylor Pothast, Ilias Gerostathopoulos, Evangelos Pournaras, Raphael E. Stern, Decentralized Optimization of Vehicle Route Planning-A Cross-City Comparative Study, Transportation Research Board 2020 Annual Meeting, 2020, (to appear)
- Evangelos Pournaras, Seoho Jung, Srivatsan Yadhunathan, Huiting Zhang, Xingliang Fang, Socio-technical Smart Grid Optimization via Decentralized Charge Control of Electric Vehicles, Applied Soft Computing, Vol. 82, pp. 105573, 2019, Elsevier
- Joval Nikolic, Evangelos Pournaras, Structural Self-adaptation for Decentralized Pervasive Intelligence, in the Proceedings of the 22nd Euromicro Conference on Digital System Design-DSD-2019, Chalkidiki, Greece, August 2019 © IEEE
- Ilias Gerostathopoulos, Evangelos Pournaras, TRAPPed in Traffic? A Self-Adaptive Framework for Decentralized Traffic Optimization, in the Proceedings of the 14th International Symposium on Software Engineering for Adaptive and Self-managing Systems-SEAMS-2019, Montreal, Canada, May 2019 © IEEE (Awarded badge: Artifacts Evaluated – Reusable)
- Evangelos Pournaras, Srivatsan Yadhunathan and Ada Diaconescu, Holarchic Structures for Decentralized Deep Learning-A Performance Analysis, Cluster Computing, 2019, Springer (to appear)
- Evangelos Pournaras, Peter Pilgerstorfer and Thomas Asikis, Decentralized Collective Learning for Self-managed Sharing Economies, ACM Transactions of Autonomous and Adaptive Systems, Vol. 13, Nr. 2, pp. 10, 2018, ACM
- Evangelos Pournaras, Mark Yao, Dirk Helbing, Self-regulating Supply-Demand Systems, Future Generation Computer Systems, Vol. 76, pp. 73-91, 2017 © Elsevier
- Peter Pilgerstorfer and Evangelos Pournaras, Self-adaptive Learning in Decentralized Combinatorial Optimization-A Design Paradigm for Sharing Economies, in the Proceedings of the 12th International Symposium on Software Engineering for Adaptive and Self-managing Systems-SEAMS-2017, Buenos Aires, May 2017
- Marinos Koutsomichalis and Evangelos Pournaras, The Sound of Decentralization-Sonifying Computational Intelligence in Sharing Economies, in the proceedings of the 23rd International Symposium on Electronic Art-ISEA-2017, Manizales, Colombia, June 2017
- Akshay Uttama Nambi, Evangelos Pournaras and RangaRao Venkatesha Prasad, Temporal Self-regulation of Energy Demand, IEEE Transactions on Industrial Informatics, Vol. 12, Nr. 3, pp. 1196-1205, 2016 © IEEE [Supplementary Information] (Nominated to IES ITeN )
- Evangelos Pournaras, Matteo Vasirani, Robert E. Kooij and Karl Aberer, Socio-technical Trade-offs in Self-regulating Smart Grids, in the proceedings of the International Conference on Computational Social Science-ICCSS 2015, Helsinki, Finland, June 2015 (compressed contribution of earlier papers)
- Evangelos Pournaras, Matteo Vasirani, Robert E. Kooij and Karl Aberer, Decentralized Planning of Energy Demand for the Management of Robustness and Discomfort, IEEE Transactions on Industrial Informatics, Vol. 10, Nr. 4, pp. 2280-2289, 2014 (to appear) © IEEE
- Evangelos Pournaras, Matteo Vasirani, Robert E. Kooij, Karl Aberer, Measuring and Controlling Unfairness in Decentralized Planning of Energy Demand, in the proceeding of the IEEE International Energy Conference-EnergyCon 2014, Dubrovnik, Croatia, May 2014. © IEEE [Presentation]
- Evangelos Pournaras, Multi-level Reconfigurable Self-organization in Overlay Services, PhD Thesis, Delft University of Technology, March 2013 (Chapter 6)
- Evangelos Pournaras, Martijn Warnier and Frances M.T. Brazier, Local Agent-based Self-stabilisation in Global Resource Utilisation, International Journal of Autonomic Computing, Vol. 1, Nr. 4, pp. 350-373, 2010 © Interscience Publishers
- Evangelos Pournaras, Martijn Warnier and Frances M.T. Brazier, A Distributed Agent-based Approach to the Stabilization of Global Resource Utilization, in the proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems-CISIS 2009, pages 185-192, Fukuoka, Japan, March 2009. © IEEE [Presentation]
- Evangelos Pournaras, Martijn Warnier and Frances M.T. Brazier, Towards Emergent Energy Synchronization using Agents, in the proceedings of the International Workshop on Agent Technologies for Energy Systems-ATES 2010, Toronto, Canada, May 2010 [Presentation]
- Evangelos Pournaras, Martijn Warnier and Frances M.T. Brazier, Using intelligent agents for self-adaptation and self-optimization of energy consumption in power networks, in the proceedings of the International Workshop on Agents for Autonomic Computing-AAC 2008, Chicago, USA, June 2008 [Presentation]
- Evangelos Pournaras, Martijn Warnier, Frances M.T. Brazier and Elth Ogston, Towards Adaptive Energy Plan Aggregation over a Peer-to-Peer Tree Overlay, in the proceedings of the Performance for Peer-to-Peer Systems Workshop-P4P2P 2008, Warwick, UK, May 2008 [Presentation]
- Evangelos Pournaras, Martijn Warnier and Frances M.T. Brazier, Energy Consumption Stabilization by Agent-Based Decentralized Tree Aggregation, poster presentation at SIREN 2008 Symposium, Vrije Universiteit Amsterdam, September 2008
- Evangelos Pournaras, Martijn Warnier and Frances M.T. Brazier, A Distributed Agent-based Approach to the Stabilization of Global Resource Utilization, in the proceedings of the 21th Belgian-Dutch Conference on Artificial Intelligence-BNAIC 2009, Eindhoven, The Netherlands, October 2009 (compressed contribution of an earlier paper) [Presentation]