paperAugust 2026Unreviewed

Watermarked Game Solving via Perturbed Regret Minimization

Juho Kim, Tuomas Sandholm

Abstract

Many real-world interactions among self-interested parties can be modeled by game theory, and the rapid advancements in AI have raised concerns about the possible misuse---accidental or deliberate---of superhuman or human-level game-playing agents by bad actors. While AI watermarking has mainly been applied to LLM-generated texts, a recent line of work proposes developing watermarking techniques for agents in game-theoretic settings. However, existing watermarking techniques for game-theoretic a

Cite

@misc{kim2026watermarked,
  title = {{Watermarked Game Solving via Perturbed Regret Minimization}},
  author = {Juho Kim and Tuomas Sandholm},
  year = {2026},
  month = aug,
  eprint = {2608.14977},
  archivePrefix = {arXiv},
  url = {https://www.semanticscholar.org/paper/d375bc8b1fa72311b4984e44877fa27413f61e2a}
}