From the 1 of 7 linked papers with an AI index.
4 papers · 1 filter
The Computable but Not Learnable Information-Value-Free Equilibria and Regulation of Algorithmic Collusion
Jason D. Hartline, Chang Wang, Chenhao Zhang
The paper shows that while certain information‑value‑free correlated equilibria can be computed efficiently, they cannot be learned online by many standard learning algorithms, hig…
Incentivizing User Data Contributions for LLM Improvement under Withdrawal Rights
Di Feng, Chenhao Zhang, Zhanzhan Zhao
The continued improvement of large language models (LLMs) increasingly depends on eliciting high-quality, user-generated data, yet such data are costly to provide and often withhel…
Regulation of Algorithmic Collusion, Refined: Testing Pessimistic Calibrated Regret
Jason D. Hartline, Chang Wang, Chenhao Zhang
We study the regulation of algorithmic (non-)collusion amongst sellers in dynamic imperfect price competition by auditing their data as introduced by Hartline et al. [2024]. We dev…
Regulation of Algorithmic Collusion
Jason D. Hartline, Sheng Long, Chenhao Zhang
Consider sellers in a competitive market that use algorithms to adapt their prices from data that they collect. In such a context it is plausible that algorithms could arrive at pr…