Leader of the group Intelligent and Autonomous Systems: Eric Pauwels.

IAS:  Learning, planning and resource allocation for intelligent, strategic agents

Research Objectives

Combining expertise from both mathematics (e.g. stochastics, game theory, operation research) and computer science (artificial intelligence, machine learning, and computation), IAS researchers conduct research in:

  • Data-efficient, robust, transferable and explainable learning, planning and resource allocation in multi-agent systems.
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  • Multi-Agent Systems and Human-AI collectives (HAIC): investigating strategic and emergent behavior in multi-agents systems or collectives comprising both humans and AI agents, involving research topics ranging from negotiation and opponent modeling, to auction bidding, mechanism design and collective decision making. 
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  • Explainable and Responsible AI
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  • Fundamental problems inspired by applications to energy systems, logistics, negotiations, and games as general models of strategic interactions.
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Research: Motivation and Context

Increasingly, our social and technological world is organised around complex systems. These are dynamic networks of interacting nodes (or agents) that continuously exchange digital or physical resources, including data or information, energy, materials and products. The agents in these systems face real challenges, as they often only have access to partial and noisy information and need to operate in a constantly changing and uncertain environment. As a consequence, there is an unrelenting pressure to improve the network’s overall performance and resilience by making the individual nodes more intelligent and autonomous.

In our research group, we study generic and fundamental mechanisms that enable the emergence of various degrees of organization, intelligence and autonomy in such systems, and apply them to concrete problems of societal relevance.

Opportunities and Community Building 



No vacancies currently.



Associated Members

Current projects with external funding

  • Lectoraat Urban Analytics (+ verlenging) ()
  • Aligning citizens and systems (full-proposal) (ALIGN4energy)
  • Coordinating Multi-deal Bilateral Negotiations (COMBINE)
  • Energy Intranets (NEAT)
  • Resilience and Cyber Security of Integrated Cyber-Physical Energy Systems (RESCUE)
  • Using small data and big data: Neighborhood Energy & Data Management Integration System (S&B NEDMIS)
  • Testing and Evaluating Sophisticated information and communication Technologies for enaBling scalablE smart griD Deployment (TESTBED-2)

Related partners

  • Alpen-Adria-Universität Klagenfurt
  • Hogeschool van Amsterdam
  • SURFsara B.V.
  • Technische Universiteit Eindhoven
  • Technische Universiteit Delft
  • University of Durham