PEAS Representation of AI agent
PEAS stands for performace measure, environment, actuators and sensors. It is a framework that is used to describe an AI agent. It’s a structured approach to design and understand AI systems.
- Perfromance measure: Performance measure is a criteria that measures the success of the agent. It is used to evaluate how well the agent is acheiving its goal.
For example, in a spam filter system, the performance measure could be minimizing the number of spam emails reaching the inbox. - Environment: The environment represents the domain or context in which the agent operates and interacts. This can range from physical spaces like rooms to virtual environments such as game worlds or online platforms like the internet.
- Actuators: Actuators are the mechanisms through which the AI agent performs actions or interacts with its environment to achieve its goals. These can include physical actuators like motors and robotic hands, as well as digital actuators like computer screens and text-to-speech converters.
- Sensors: Sensors enable the AI agent to gather information from its environment, providing data that informs its decision-making process and actions. These sensors can capture various environmental parameters such as temperature, sound, movement, or visual input. Examples of sensors include cameras, microphones, temperature sensors, and motion sensors.
Intelligent Agent in AI
In the realm of AI, Intelligent Agents stand as pivotal entities, driving automation and decision-making with cognitive abilities. This article explores the concept, architecture, functionalities, and real-world applications of these agents, shaping the modern AI landscape.
Table of Content
- Understanding Intelligent Agents
- Rational Agents and Rationality in Decision-Making
- How Intelligent Agent work Inside?
- PEAS Representation of AI agent
- Applications of Intelligent Agents
- Challenges for Intelligent Agents
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