By Architectural Components, I mean, how the agent makes decisions. The levels describe the core components of an AI agent and how it processes information. These include agents like Simple Reflex, Model-Based Reflex, Goal-Based, and Learning Agents. Let’s just get familiar with these before we develop agents in the future blogs.
- Simple Reflex Agents: Respond directly to current inputs without considering past experiences or future goals.
- Model-Based Reflex Agents: Maintain an internal model of the environment to handle partially observable situations and make more informed decisions.
- Goal-Based Agents: Use their models to search for sequences of actions that achieve specific goals, providing a sense of purpose.
- Utility-Based Agents: Go beyond goals to choose actions that maximize a “utility function,” leading to more rational and optimal outcomes.
- Learning Agents: Can improve their performance over time by learning from their experiences and interactions with the environment.