What Are Agents?
Agents in AI are computer programs that observe their environment through sensors and then take action through actuators. Agents are how an AI system focuses on achieving its goal.
Take AI as a human brain and agents as its parts i.e. hands, legs, etc. The difference is that each agent based on its type is capable of taking actions on its own. Many such agent actions then combine to complete a larger task at hand.
Agents interact with other agents as well as agents interact with the environment.
Different types of agents are Simple reflex agents, Goal-based agents, Model-based agents, Utility agents, etc.
Examples of agents are:
- An internet shopping agent. Where sensors are HTML or XHTML pages and actuators display of URLs to the user.
- A chatbot agent that takes human responses as sensors and displays answers or fetches URLs as actuators.
Perception in AI Agents
Perception stands as a foundational concept in the realm of AI, enabling agents to glean insights from their environment through sensory inputs. From visual interpretation to auditory recognition, perceptions empower AI agents to make informed decisions, adapt to dynamic conditions, and interact meaningfully with their surroundings. In this discourse, we explore the pivotal role of perceptions in shaping the capabilities of AI agents and driving advancements in artificial intelligence.
Table of Content
- What Are Agents?
- What is Perception in AI Agents?
- Terminologies Associated with Perception In AI Agents
- Steps involved in building the perception of an AI Agents
- Types of Perception in AI Agents
- Role of Perceptions In AI Agents