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
More information and research projects
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

No vacancies currently.

News

Tim Baarslag joins The Young Academy

CWI researcher Tim Baarslag has been appointed as a new member of The Young Academy. Starting in 2020, he will join this platform for young scientists who are recognised internationally for their talent. The Young Academy is an independently operating platform within the Royal Netherlands Academy of Arts and Sciences (KNAW).

Tim Baarslag joins The Young Academy - Read More…

CWI signs partnership for Meaningful Control of Autonomous Systems

Together with TNO and the University of Amsterdam, CWI initiates a new research collaboration to study the impact of autonomous systems in society and the adoption of AI-based systems. Today, the three members are signing a letter of intent, called Meaningful Control of Autonomous Systems (MCAS).

CWI signs partnership for Meaningful Control of Autonomous Systems - Read More…

Tim Baarslag selected for ‘FD Young Talents 2019’

Tim Baarslag of CWI’s Intelligent and Autonomous Systems group has been selected by the Dutch newspaper Het Financieele Dagblad (FD) as one of the most promising Young Talents of 2019.

Tim Baarslag selected for ‘FD Young Talents 2019’ - Read More…

Best Early-Researcher Paper Award for Tim Baarslag

Tim Baarslag of CWI's Intelligent and Autonomous Systems group has been awarded with the "Best Early-Researcher Paper Award" at the Agreement Technologies (AT2018) conference in Bergen, Norway.

Best Early-Researcher Paper Award for Tim Baarslag - Read More…

Members

Associated Members

Current projects with external funding

Framework for demand-supply matching and ancillary service provision through distributed energy resources (project D) ()
Lectoraat Urban Analytics (+ verlenging) ()
Advanced Planning & Scheduling (APS)
Flexible Assets Bid Across Markets (FABAM)
Heat and Power Systems at Industrial Sites and Harbours (HaPSISH)
Energy Intranets (NEAT)
Developing algorithms for testing and use on Acumex's platform (PPS ACUMEX)
Representing Users in a Negotiation (RUN): An Autonomous Negotiator Under Preference Uncertainty (RUN)
Using small data and big data: Neighborhood Energy & Data Management Integration System (S&B NEDMIS)