5 papers
The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment
Filippo Tonini, Federico Torrielli, Anton Danholt Lautrup +3
As AI systems built from multiple language-model agents become more common, they are increasingly used to make decisions together: discussing, negotiating, and acting on shared tas…
Hitting Time Isomorphism for Multi-Stage Planning with Foundation Policies
Magnus Victor Boock, Abdullah Akgül, Mustafa Mert Ãelikok +1
We present a new operator-theoretic representation learning framework for offline reinforcement learning that recovers the directed temporal geometry of a controlled Markov process…
A Measure-Theoretic Finite-Sample Theory for Adaptive-Data Fitted Q-Iteration
Manuel Haussmann, Mustafa Mert Ãelikok, Melih Kandemir
While reinforcement learning (RL) promises to revolutionize the control of complex nonlinear robotic systems, a profound gap persists between the heuristic success of model-free of…
Distributional Active Inference
Abdullah Akgül, Abdullah Akgül, Gulcin Baykal +5
Optimal control of complex environments with robotic systems faces two complementary and intertwined challenges: efficient organization of sensory state information and far-sighted…
SHARPIE: A Modular Framework for Reinforcement Learning and Human-AI Interaction Experiments
Hüseyin Aydın, Kevin Godin-Dubois, Libio Goncalvez Braz +6
Reinforcement learning (RL) offers a general approach for modeling and training AI agents, including human-AI interaction scenarios. In this paper, we propose SHARPIE (Shared Human…