Search Results for author:
Found 8 papers, 3 papers with code
Recursive Joint Simulation in Games
In this paper, we study an interaction between AI agents where the agents run a recursive joint simulation.
A Theory of Bounded Inductive Rationality
In this paper, we develop a theory of rational decision making that does not assume logical omniscience.
The Computational Complexity of Single-Player Imperfect-Recall Games
For such games, two natural equilibrium concepts have been proposed as alternative solution concepts to ex-ante optimality.
Incentivizing honest performative predictions with proper scoring rules
We show that, for binary predictions, if the influence of the expert's prediction on outcomes is bounded, it is possible to define scoring rules under which optimal reports are arbitrarily close to fixed points.
For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria
In this work, we show that any locally optimal symmetric strategy profile is also a (global) Nash equilibrium.
Reinforcement Learning in Newcomblike Environments
This gives us a powerful tool for reasoning about the limit behaviour of agents -- for example, it lets us show that there are Newcomblike environments in which a reinforcement learning agent cannot converge to any optimal policy.
A New Formalism, Method and Open Issues for Zero-Shot Coordination
We introduce an extension of the algorithm, other-play with tie-breaking, and prove that it is optimal in the LFC problem and an equilibrium in the LFC game.
Formalizing Preference Utilitarianism in Physical World Models
Most ethical work is done at a low level of formality.
