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The Algorithmic Learning in Games seminar is a joint effort between faculty at London School of Economics, the University of Waterloo, Imperial College London and, King's College London.
We meet once every fortnight to discuss problems and research in a range of topics related to:
Game Theory
Multi-Agent Reinforcement Learning
Learning in Games
Multi-Agent Systems
Recordings of our past sessions can be found here.
Next Talk
Our next talk will be lead by Debmalya Mandal on November 10th 2025 at 16:00 GMT. Please see further details below:
Performative Reinforcement Learning
Performative Reinforcement Learning
Debmalya Mandal - Assistant Professor, University of Warwick
How should we design machine learning systems when the underlying environment (e.g. data distribution) changes in response to the deployed model? In the context of supervised learning, the framework of performative prediction provides game-theoretic solution concepts that a learner can optimize in the presence of decision-dependent distributions. In this talk, I will provide an overview of our work to model such “performativity” in the context of reinforcement learning. In particular, I will describe how to reach a stable policy in a setting where the underlying Markov Decision Process (MDP) reacts to the deployed policy. I will then discuss some of our recent efforts to extend this framework of performative RL to multi-agent settings and corrupted feedback.
Organisers
London School of Economics
University of Waterloo
Imperial College London
King's College London
Schedule
We intend to meet every other Monday from 16:00 - 17:00 GMT - please allow for slight changes to this schedule as needed.
Upcoming Speakers
Past Speakers
Recordings of past sessions can be found here or via the title of the respective talk in the spreadsheet below.
Sign-Up Form
We are open to any interested in joining the seminar, both as a member of the audience and as a speaker. To get in touch, please fill out the form below and we will get back to you as soon as possible.
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