AI Agent Glossary
Deep dive into the types, architectures, and foundations of modern AI agents. Whether you're a founder or a developer, these definitions help you build smarter.
In AI, a rational agent is one that acts so as to achieve the best outcome or, when there is uncertainty, the best expected outcome. It is a fundamental concept in the foundations of computational agents.
An autonomous entity which observes through sensors and acts upon an environment using actuators. It directs its activity towards achieving goals.
An AI agent that can perform tasks and make decisions on its own without constant human intervention. It is 'composed of' an architecture and a program.
An agent that acts to achieve specific goals. They use knowledge about the environment to choose actions that lead to the desired state.
An agent that can improve its own performance over time. It consists of a learning element, a performance element, a critic, and a problem generator.
A computerized system composed of multiple interacting intelligent agents. MAS can solve problems that are difficult or impossible for an individual agent or a monolithic system.
An agent that uses a 'model' of the world to handle partial observability. It keeps track of the current state of the world using internal state.
Agents that maintain an internal 'knowledge base' and reason about that knowledge to perform actions.
An intelligent virtual agent designed specifically for natural language interaction with humans, often used in customer support or virtual assistance.
An agent whose decisions are made via logical deduction from a knowledge base of facts and rules.
Why AI Agents Matter for Your Business
Understanding the types of agents in AI—from simple reflex agents to complex learning multi-agent systems—is the first step in building an autonomous business. At Jalpa, we specialize in implementing Intelligent Virtual Agents and Conversational AI that don't just chat, but execute tasks.