7https://github.com/Torantulino/Auto-GPT
8https://github.com/yoheinakajima/babyagi

19

3.3 Training Models for Improved Tool Learning

Figure 7: Training strategies for tool learning: (left) learning from human-annotated or model-annotated
demonstrations; (right) learning from feedback, where the supervision could come from either the environment
or humans.

abilities and expertise. Multi-agent collaboration can pave the way for more effective and efﬁcient
problem-solving, which may involve designing methods for communication, coordination, and negoti-
ation among agents to ensure seamless collaboration and optimal task execution. Recently, Park et al.
(2023) show that multiple agents modeled with foundation models can simulate human behaviors (e.g.,
interpersonal communication) in interactive scenarios, which provides promising evidence for employing
multiple agents for tool learning.
Tool Learning with Foundation Models