Crypto Ticker:
technology from Arxiv cs.ai

Regret Minimization with Adaptive Opponents in Repeated Games

Mingyang Liu, Asuman Ozdaglar, Tiancheng Yu, Kaiqing Zhang
Jun 5, 2026 at 04:00
9 Views
0 Comments

arXiv:2606.06486v1 Announce Type: cross Abstract: In this paper, we study regret minimization in repeated games with \emph{adaptive} opponents who can respond based on histories of play. The standard metric of \emph{external regret} in online learning is known to fail to capture such adaptivity. To account for players' counterfactual reasoning,...

Read the full article at the source.

Was this helpful?
Share:

Comments (0)

Please login to post a comment

No comments yet. Be the first to comment!