collaborators

12 papers

cs.AI2026

A dataset of rated conceptual arguments

Emery Cooper, Caspar Oesterheld, Linh Chi Nguyen +2

The paper introduces a dataset of 951 expert‑rated argumentative critiques on 442 position texts covering AI safety, decision theory, ethics, and politics, and uses it to benchmark…

cs.AI2026

Recursive Joint Simulation in Games

Vojtech Kovarik, Caspar Oesterheld, Vincent Conitzer

Game-theoretic dynamics between AI agents could differ from traditional human-human interactions in various ways. One such difference is that it may be possible to accurately simul…

cs.AI2026

Implementing surrogate goals for safer bargaining in LLM-based agents

Caspar Oesterheld, Maxime Riché, Filip Sondej +2

Surrogate goals have been proposed as a strategy for reducing risks from bargaining failures. A surrogate goal is goal that a principal can give an AI agent and that deflects any t…

cs.GT2026

How Many Votes is a Lie Worth? Measuring Strategyproofness through Resource Augmentation

Ratip Emin Berker, Vincent Conitzer, Eden Hartman +2

It is well known, by the Gibbard-Satterthwaite Theorem, that when there are more than two candidates, any non-dictatorial voting rule can be manipulated by untruthful voters. But h…

cs.GT2025

Choosing What Game to Play without Selecting Equilibria: Inferring Safe (Pareto) Improvements in Binary Constraint Structures

Caspar Oesterheld, Vincent Conitzer

We consider a setting in which a principal gets to choose which game from some given set is played by a group of agents. The principal would like to choose a game that favors one o…

cs.GT2025

Promises Made, Promises Kept: Safe Pareto Improvements via Ex Post Verifiable Commitments

Nathaniel Sauerberg, Caspar Oesterheld

A safe Pareto improvement (SPI) [41] is a modification of a game that leaves all players better off with certainty. SPIs are typically proven under qualitative assumptions about th…