Skip to content
Log in
Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Kihyun Yu

View on Semantic Scholar

3 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Preprint Oct 2026

Rate-Optimal Algorithm for Adversarial Linear CMDPs

We study episodic adversarial linear constrained Markov decision processes (CMDPs) with unknown transitions, where both the loss and constraint functions may vary adversarially across episodes. The best previous algorithm achieves $\widetilde{\mathcal{O}}(K^{3/4})$ regret and cumulative constraint violation, leaving a...

Kihyun Yu, Hong-Hao Wei, Dabeen Lee · 0 citations
#machine learning Preprint Oct 2026

Rate-Optimal Algorithm for Adversarial Linear CMDPs

We study episodic adversarial linear constrained Markov decision processes (CMDPs) with unknown transitions, where both the loss and constraint functions may vary adversarially across episodes. The best previous algorithm achieves $\widetilde{\mathcal{O}}(K^{3/4})$ regret and cumulative constraint violation, leaving a...

Kihyun Yu, Hong-Hao Wei, Dabeen Lee · 0 citations
#machine learning Preprint Sep 2026

Learning Infinite-Horizon Average-Reward CMDPs via State Augmentation

We study infinite-horizon average-reward constrained Markov decision processes (CMDPs) under the weakly communicating assumption. Existing high-probability guarantees for this setting either require computationally inefficient algorithms or have suboptimal dependence on the number of interactions $T$. We propose, to th...

Kihyun Yu, Seoungbin Bae, Dabeen Lee · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.