Beginner · Reinforcement Learning
Act
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. The stage in an agent's loop where it executes a chosen action, like sending an API request.
Technical Definition
The stage in an agent's loop where it executes a chosen action, like sending an API request.
How it works
In the context of agent-based systems, 'act' refers to the execution phase where the agent carries out the action it decided upon during the 'reasoning' or 'planning' stage. This could involve interacting with the environment, making a decision, or sending a command, such as executing an API call. It is the step where the agent's intentions are translated into real-world or digital effects.
Related Concepts
- Reinforcement Learning — A paradigm where an agent learns to make decisions by receiving rewards or penalties from its environment through trial and error.
- AI Agent — An AI system that autonomously plans, uses tools, and takes actions to accomplish goals through iterative reasoning.
- Agentic loop — An agentic loop is a cycle where an agent observes, reasons, acts, and receives feedback until a set goal is met.
- Tool Use — The ability of an AI model, especially an LLM agent, to autonomously identify, select, and utilize external tools and APIs to accomplish tasks.