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Planning Against Learning in Rank-1 Games
William Overman
Learning algorithms are often used to make decisions in repeated multi-agent environments. When another player understands how a learner adapts from past experience, that player ca…
Calibrating Conservatism for Scalable Oversight
William Overman, Mohsen Bayati
Agentic AI systems capable of autonomous planning and extended environmental interaction pose a fundamental control problem: how can humans maintain meaningful oversight of systems…
Annealed Softmax Greedy in Many-Armed Bayesian Bandits
William Overman, Mohsen Bayati
Reinforcement learning with verifiable rewards and group-based policy optimization methods update a stochastic policy by sampling multiple completions per prompt and increasing the…
Causal Effects with Unobserved Unit Types in Interacting Human-AI Systems
William Overman, Sadegh Shirani, Mohsen Bayati
We study experiments on interacting populations of humans and AI agents, where both unit types and the interaction network remain unobserved. Although causal effects propagate thro…