Description

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.
More information and research projects
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.
More information and research projects
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.
More information and research projects

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

Seminars For more information on our seminars, visit the seminar webpage.
Internships We invite talented Master's and PhD candidates to have a look at our internships.
Supporting the AI community We strongly believe that successful research is a community effort to which we want to contribute:
- Presentations and educational material
- Organisational and community-building activities

Vacancies

PhD‘s on sample-based planning and learning, and computational social sciences

PhD students, on the subjects of sample-based planning, reinforcement learning, explainable AI, and computational social sciences.

PhD‘s on sample-based planning and learning, and computational social sciences - Read More…

News

Members

Associated Members

Current projects with external funding

Lectoraat Urban Analytics (+ verlenging) ()
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
INRIA
Hogeschool van Amsterdam
SURFsara B.V.
Technische Universiteit Eindhoven
Technische Universiteit Delft
University of Durham