EvoAgent: A Generic Method to Automatically Extend Expert Agents to Multi-Agent Systems via the Evolutionary Algorithm
What are Large Language Models (LLMs) used for?
Large Language Models (LLMs) are used for various tasks such as language understanding, reasoning, and generation. They can be applied in chatbots, virtual assistants, content generation, research assistance, and language translation. LLMs have the ability to infer from context, generate coherent and contextually relevant responses, and assist in creative writing or code generation tasks. They are utilized across industries for streamlining processes, improving customer experiences, and enabling efficient decision-making.
How do multi-agent systems simulate human behavior?
Multi-agent systems simulate human behavior by using multiple autonomous agents that interact with each other and their environment. These agents are designed to mimic human decision-making processes, social interactions, and problem-solving strategies. They use various techniques such as machine learning, evolutionary algorithms, and game theory to generate diverse and realistic behaviors. By collaborating and competing with each other, these agents can replicate complex social phenomena and provide valuable insights into human behavior.
What limits the scalability of current multi-agent designs?
The scalability of current multi-agent designs is limited by their reliance on handcrafted settings, which require expensive human labor3. This approach restricts adaptability and constrains the task scope, highlighting the need for more flexible, automated methods.