Fwd: S3D Seminar Series: Yi Wu - Friday 12/8 at 12pm - Language Model meets Reinforcement Learning: Building Strong Language Agents for Strategic Gameplay

[Asher Trockman]

---------- Forwarded message ---------
From: Linda Campbell <lv2c at andrew.cmu.edu>
Date: Thu, Nov 30, 2023 at 9:57 AM
Subject: S3D Seminar Series: Yi Wu - Friday 12/8
To: <s3d-seminar at cs.cmu.edu>


S3D Seminar Series



Friday, December 8, 2023

12:00 p.m. – 1:15 p.m.  Google calendar
<https://calendar.google.com/calendar/event?action=TEMPLATE&tmeid=MDYzM210bjJlcjIyaXBkdGRlY2M4NHV1Y2MgYW5kcmV3LmNtdS5lZHVfbjBscGtkaWFyYTJhdWhqaXVjbmpsbmVoYzhAZw&tmsrc=andrew.cmu.edu_n0lpkdiara2auhjiucnjlnehc8%40group.calendar.google.com>

In person at TCS 358

Or online via Zoom:
https://cmu.zoom.us/j/93910552516?pwd=S1hRUXhJendVYzBEUC94dlNvd0Y2UT09
*Lunch provided starting at 11:45 a.m.*

*Title: * Language Model meets Reinforcement Learning: Building Strong
Language Agents for Strategic Gameplay

*Speaker:  *Yi Wu, Assistant Professor, Institute for Interdisciplinary
Information Sciences (IIIS), Tsinghua University

*Abstract:*  Thanks to the advances in large language models (LLM), there
has been a recent trend to develop intelligent language agents for complex
tasks. Most existing applications of language agents are purely LLM-based,
i.e., by directly prompting LLMs to output actions. Although interesting
emergent behaviors can be observed, their performances in complex
multi-agent games can be limited due to the lack of domain-specific
training. This talk will cover some recent projects in my group on
developing language agents that can both yield strong gameplay performances
and cooperate with real human players in challenging multi-agent games. The
key idea is to combine language modeling and reinforcement learning. The
language model will serve as an interface for reasoning and interpreting
high-level commands while reinforcement learning helps substantially
improve the gameplay performance of the agent. We demonstrate our agents in
three domains, including an agent that can follow high-level commands to
play a real-time strategy game, an Overcooked agent that can cooperate with
humans via languages to cook dishes, and an agent that outperforms average
human players in the Werewolf game.

*Bio: * Yi Wu is now an assistant professor at the Institute for
Interdisciplinary Information Sciences (IIIS) at Tsinghua University.
He obtained his Ph.D. degree from UC Berkeley in 2019 under the
supervision of Prof. Stuart Russell. Before moving back to Tsinghua,
Yi was a full-time researcher at OpenAI. His research focuses on
improving the generalization capabilities of learning agents. He is
broadly interested in a variety of topics in AI, including multi-agent
reinforcement learning, human-AI interaction, language grounding, and
robot learning. His representative works include the MADDPG/MAPPO
algorithm, OpenAI's hide-and-seek project, and the value iteration
network, which won the best paper award at NIPS 2016.





*Upcoming S3D Seminar Series Talks*

February 7:  George Fairbanks*

TBD:  Yesemin Acar*

April 17:  Mani Srivastava*

April 24:  Premkumar Devanbu*

May 1:  David Rand* (joint with CSS)



*indicates part of the Distinguished Speakers Series
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