Partially Observable Zero-shot coordination by Predicting Intention of Partner

Jinnyeong Yang, Yuhwan Jeong, Hoyong Kwon, Minseok Kim, Jihun Kim +1 more
10/6/2026
cs.AIcs.MA

No confident code implementation found for this paper.

Abstract

Zero-shot coordination in embodied settings requires acting while the partner is intermittently out of view, leaving existing methods with ambiguous partner representations and uncertainty over hidden partner states. We propose Predicting Intention of Partner (PIP) to jointly address these challenges. PIP uses a Joint-view VAE to distill richer training-time evidence from the union of both agents' local observations into a partner representation available from local observations alone. Partner-state Belief networks further infer the partner's hidden location and behavioral tendencies from the ego agent's interaction history. We evaluate PIP in Burrito-PO, Overcooked-PO, and a Melting Pot substrate, together with a human evaluation in Burrito-PO. PIP attains the highest mean performance among the compared methods across all three benchmarks. Human evaluation and diagnostic analyses further support coordination with unseen partners and the contributions of both components under partner occlusion.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{yang2026partially,
  title  = {Partially Observable Zero-shot coordination by Predicting Intention of Partner},
  author = {Jinnyeong Yang and Yuhwan Jeong and Hoyong Kwon and Minseok Kim and Jihun Kim and Kuk-Jin Yoon},
  year   = {2026},
  eprint = {2610.08142},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2610.08142v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2610.08142.svg)](https://codeofpaper.com/paper/2610.08142)

Discussion