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--- plan_and_execute_agents [2026/03/24 17:00] – Add Python code example for LangGraph plan-and-execute agent agent
+++ plan_and_execute_agents [2026/03/24 22:12] (current) – Add References section with Plan-and-Solve, ReAct, BabyAGI, and LangChain refs agent
@@ Line 134: / Line 134: @@
   * Process reward models for evaluating plan quality
   * Frameworks like LangGraph, CrewAI, and AutoGen providing built-in plan-and-execute primitives
+===== References =====
+  * [[https://arxiv.org/abs/2305.04091|Wang, L. et al. "Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models."]] arXiv:2305.04091, 2023.
+  * [[https://arxiv.org/abs/2210.03629|Yao, S. et al. "ReAct: Synergizing Reasoning and Acting in Language Models."]] arXiv:2210.03629, 2022.
+  * [[https://arxiv.org/abs/2305.10601|Yao, S. et al. "Tree of Thoughts: Deliberate Problem Solving with Large Language Models."]] arXiv:2305.10601, 2023.
+  * [[https://arxiv.org/abs/2303.11366|Shinn, N. et al. "Reflexion: Language Agents with Verbal Reinforcement Learning."]] arXiv:2303.11366, 2023.
+  * [[https://github.com/yoheinakajima/babyagi|GitHub: yoheinakajima/babyagi]] -- Original BabyAGI task-driven agent by [[https://yoheinakajima.com|Yohei Nakajima]].
+  * [[https://python.langchain.com/docs/how_to/|LangChain Documentation]] -- Plan-and-execute patterns via LangGraph.
+  * [[https://arxiv.org/abs/2308.11432|Wang, L. et al. "A Survey on Large Language Model based Autonomous Agents."]] arXiv:2308.11432, 2023.
 ===== See Also =====

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