The ongoing AI revolution raises many questions. Are the current large language models intelligent? Are they becoming super intelligent? What is the role, if any, of logic in the current AI? Wh...
The FOAM Seminar, organised by computer scientists at the ILLC, features research on questions of a fundamental nature in computer science and AI, in research areas such as algorithms, optimisation, data management, planning, knowledge representation, and multiagent systems. Talks are intended to be broadly accessible and pitched at the level you might find at a plenary talk of a relevant conference (such as IJCAI, AAAI, KR, ICAPS, AAMAS, EC, PODS, LICS, STOC, FOCS, and SODA).
FOAM usually takes place on a Friday at 15:00. Talks are roughly 45 minutes long, followed by a brief discussion. Afterwards, you are invited to stay for a chat and a drink. Everyone is welcome to attend!
If you want to receive automatic updates on our talks, you can either (1) use our RSS feed, (2) its cal version, or (3) subscribe to the our mailing list.
Upcoming Talks
Past Talks
Bernhard Nebel
(University of Freiburg)
On the Computational Complexity of Multi-Agent Pathfinding on Directed Graphs
“Multi-agent pathfinding”, also called “pebble motion on graphs” or “cooperative pathfinding”, is the problem of deciding the existence of or generating a collision-free movement plan for a set of ...
Emir Demirovic
(TU Delft)
Decision trees in a formal world: machine learning (with constraints), controller verification, and unsatisfiability proofs for graph problems
Decision trees are an effective and concise way of conveying information, easily understood by virtually everyone regardless of the topic. Given the recent interest in explainable AI and related fi...
Michael Benedikt
(University of Oxford)
Logic and asymptotic combinatorics of Graph Neural Networks
Graph neural networks (GNNs) are the predominant architectures for a variety of learning tasks on graphs. We present a new angle on the expressive power of GNNs by studying how the predictions of a...
Tim van Erven
(KdVI)
How Fast Can We Compute (Approximate) Nash Equilibria in Zero-sum Matrix Games?
Nash equilibria have been central to game theory since Von Neumann, but how fast can we compute them? The best known upper bound is achieved by letting a minimizing and a maximizing online learning...
Kristin Yvonne Rozier
(Iowa State University)
On the Effectiveness of Mission-time Linear Temporal Logic (MLTL) in AI Applications
Temporal logics have become essential tools of many AI applications, from verification to planning to synthesis. Mission-time Linear Temporal Logic (MLTL) adds closed-interval integer bounds on the...
Matthijs Spaan
(TU Delft)
Exploiting Epistemic Uncertainty for Deep Exploration in Reinforcement Learning
In this talk I discuss how estimating and propagating epistemic uncertainty benefits generalization and deep exploration in reinforcement learning (RL) by focusing on two recent contributions. Fir...
Yasamin Nazari
(VU)
Distance Structures and their Algorithmic Applications
In recent years there has been a growing interest in studying graph theoretical structures used for designing efficient algorithms in various computational models, such as dynamic, parallel and dis...
Andreas Niskanen
(University of Helsinki)
SAT-based Judgment Aggregation
Judgment aggregation (JA) offers a generic formal logical framework for modeling various settings where agents must reach joint agreements through aggregating the preferences, judgments, or beliefs...
Malvin Gattinger
(ILLC)
The Limits to Gossip: Second-order Shared Knowledge of all Secrets is Unsatisfiable
It is known that without synchronization via a global clock one cannot obtain common knowledge by communication. Moreover, it is folklore that without exchanging higher-level information arbitrary ...
Daira Pinto Prieto
(ILLC)
Multi-Layer Belief Model: Justified Belief for Uncertain and Conflicting Evidence
One problem to solve in the context of information fusion, decision-making, and other artificial intelligence challenges is to compute justified beliefs based on evidence. In real-life examples, th...
Ulle Endriss
(ILLC)
Automated Reasoning for Economic Theory
The research area of computational social choice deals with the application of techniques from computer science and AI to the design and analysis of economic mechanisms for collective decision maki...
Wan Fokkink
(VU)
Supervisor Synthesis: Turning Automata into Control Software
Supervisory Control Theory, initiated by Ramadge and Wonham, automatically transforms a formal system model and its safety requirements into a (minimally) restricted system that satisfies all safet...
Guido Schäfer
(ILLC/CWI)
Social Welfare Loss in Hybrid Multi-Unit Auctions
Corruption in auctions, where an auctioneer engages in bid rigging with one (or several) of the bidders, occurs rather frequently in practice, especially in the public sector (e.g., in constructi...
Balder ten Cate
(ILLC)
Data examples
Examples can be a useful tool when a formal specification must be synthesized or communicated. They sometimes provide a more convenient medium for communication than the formal specification itsel...
Rebecca Reiffenhäuser
(ILLC)
Round-Robin Beyond Additive Agents: Existence and Fairness of Approximate Equilibria
(or how to be fair to deceptive egoists.) When allocating indivisible goods to a number of selfish agents, both fairness and truthfulness are main concerns: the allocation should guarantee everyon...
Gregor Behnke
(ILLC)
Lifted Classical Planning via Propositional Logic Satisfiability
Planning models are usually defined in lifted, i.e., first order formalisms, while most solvers need (variable-free) grounded representations. Though techniques for grounding prune unnecessary part...