Intro to Agents
Agents are intelligent systems or components that utilize Large Language Models (LLMs) to perform tasks in a dynamic and autonomous manner. Here's a breakdown of the key concepts:
What Are Agents?
- Step-by-Step Thinking: Agents leverage LLMs to think and reason through problems in a structured way, often referred to as chain-of-thought reasoning. This allows them to plan, evaluate, and execute tasks effectively.
- Access to Tools: Agents can utilize external tools (e.g., calculators, databases, APIs) to enhance their decision-making and problem-solving capabilities.
- Access to Memory: Agents can store and retrieve context, enabling them to work on tasks over time, adapt to user interactions, and handle complex workflows.
Key characteristics of AI agents include:
Perception: The ability to gather information from their environment through sensors or data inputs.
Decision-making: Using AI algorithms to process information and determine the best course of action.
Action: The capability to execute decisions and interact with the environment or users.
Learning: The ability to improve performance over time through experience and feedback.
Autonomy: Operating independently to some degree, without constant human intervention.
Goal-oriented: Working towards specific objectives or tasks.
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