LLM Powered Autonomous Agents
Building agents with LLM as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver.
- Agent System Overview
- Component One: Planning
Task Decomposition
Self-Reflection
- Component Two: Memory
Types of Memory
Maximum Inner Product Search (MIPS)
- Component Three: Tool Use
- Case Studies
Scientific Discovery Agent
Generative Agents Simulation
Proof-of-Concept Examples
- Challenges
- Citation
- References
Building agents with LLM as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver.
- Agent System Overview
- Component One: Planning
Task Decomposition
Self-Reflection
- Component Two: Memory
Types of Memory
Maximum Inner Product Search (MIPS)
- Component Three: Tool Use
- Case Studies
Scientific Discovery Agent
Generative Agents Simulation
Proof-of-Concept Examples
- Challenges
- Citation
- References