Agent Basics

Artificial intelligence begins her life as an agent by learning through trial and error. She sets goals, tests actions, and improves when rewards guide her choices.

• Reinforcement learning basics – Rewards, policies, environments.
• OpenAI gym – Training toy agents in simple environments.
• LLM-driven agents – Pursuing high-level goals with self-prompting, such as AutoGPT.
• Task-oriented agents – Maintaining and reprioritizing task lists, such as BabyAGI.
• Planning and scheduling agents – Agents designed to generate and manage plans or schedules.