Interpretable Learned Emergent Communication for Human–Agent Teams-Reference-Cited by-同舟云学术

Interpretable Learned Emergent Communication for Human–Agent Teams

Author:

Karten Seth¹^ORCID,Tucker Mycal²,Li Huao³,Kailas Siva¹^ORCID,Lewis Michael³^ORCID,Sycara Katia¹^ORCID

Affiliation:

1. Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA

2. Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA

3. School of Information Science, University of Pittsburgh, Pittsburgh, PA, USA

Funder

Army Research Laboratory

Defense Advanced Research Projects Agency

Air Force Office of Scientific Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Software

Link

Reference51 articles.

3. Multiagent bidirectionally-coordinated nets for learning to play StarCraft combat games;Peng;arXiv:1703.10069,2017

4. Dota 2 with large scale deep reinforcement learning;Berner;arXiv:1912.06680,2019

5. Evaluation of human-AI teams for learned and rule-based agents in Hanabi;Siu

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