4 papers · 1 filter
One Frozen Simulator Is Not Enough: Simulator Collapse in Multi-Agent RL
Simon Yu, Nicholas Tomlin, Marwa Abdulhai +7
Multi-agent reinforcement learning for human-AI interaction typically relies on a single large language model to simulate user behavior. We show that this approach systematically f…
Calibrate-Then-Act: Cost-Aware Exploration in LLM Agents
Wenxuan Ding, Nicholas Tomlin, Greg Durrett
LLM agents are deployed in environments where they must interact to acquire information. In these scenarios, the agent must reason about inherent cost-uncertainty tradeoffs in how…
Efficacy of Language Model Self-Play in Non-Zero-Sum Games
Austen Liao, Nicholas Tomlin, Dan Klein
Game-playing agents like AlphaGo have achieved superhuman performance through self-play, which is theoretically guaranteed to yield optimal policies in competitive games. However,…
Decision-Oriented Dialogue for Human-AI Collaboration
Jessy Lin, Nicholas Tomlin, Jacob Andreas +1
We describe a class of tasks called decision-oriented dialogues, in which AI assistants such as large language models (LMs) must collaborate with one or more humans via natural lan…