no code implementations • 29 May 2023 • Robert Loftin, Mustafa Mert Çelikok, Frans A. Oliehoek
Multiagent systems deployed in the real world need to cooperate with other agents (including humans) nearly as effectively as these agents cooperate with one another.
no code implementations • 7 Feb 2023 • Robert Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, Frans A. Oliehoek
A natural solution concept for many multiagent settings is the Stackelberg equilibrium, under which a ``leader'' agent selects a strategy that maximizes its own payoff assuming the ``follower'' chooses their best response to this strategy.
1 code implementation • 29 Nov 2022 • Alex Hämäläinen, Mustafa Mert Çelikok, Samuel Kaski
Probabilistic user modeling is essential for building machine learning systems in the ubiquitous cases with humans in the loop.
1 code implementation • 1 Jul 2022 • Miguel Suau, Jinke He, Mustafa Mert Çelikok, Matthijs T. J. Spaan, Frans A. Oliehoek
Due to its high sample complexity, simulation is, as of today, critical for the successful application of reinforcement learning.
no code implementations • 3 Apr 2022 • Mustafa Mert Çelikok, Frans A. Oliehoek, Samuel Kaski
Centaurs are half-human, half-AI decision-makers where the AI's goal is to complement the human.
no code implementations • 1 Dec 2019 • Mustafa Mert Çelikok, Tomi Peltola, Pedram Daee, Samuel Kaski
Understanding each other is the key to success in collaboration.
1 code implementation • NeurIPS 2019 • Tomi Peltola, Mustafa Mert Çelikok, Pedram Daee, Samuel Kaski
We formulate this sequential teaching problem, which current techniques in machine teaching do not address, as a Markov decision process, with the dynamics nesting a model of the learner and the actions being the teacher's responses.