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PEAS Descriptors of Task Environment
Artificial intelligence (AI) is the capacity of a machine created artificially to think and act logically or human-like. The study of the rational agent and its surroundings can be used to define an AI system. Agents use sensors to perceive their surroundings and actuators to take action on it. Knowledge, belief, purpose, and other mental attributes can exist in an AI agent. AI agents are directly related to PEAS. In this piece, we'll take a closer look at PEAS and some of its examples.
What are PEAS Descriptors?
PEAS is an AI agent representation system that focuses on evaluating the performance of the environment, sensors, and actuators. We need to be aware of our job environment to create an agent. The PEAS system aids in defining the task environment. Performance, Environment, Actuators, and Sensors are abbreviated as PEAS. AI algorithms can be written more effectively by identifying PEAS.
Agents are devices that work in the environment to accomplish specific predetermined tasks. They can be hardware, software, or a mix of the two. An intelligent agent does action independently and endures for a longer time. To achieve a certain aim, it needs also to be flexible. Agents interact with their surroundings through actuators and experience it through sensors. One agent or several agents can be present in an environment.
We will examine each PEAS component separately.
Performance − If the agent's performance is being evaluated by an objective function. Things that we can use to measure an agent's performance.
Environment − The environment refers to the agent's immediate surroundings at the time the agent is working in that environment. Depending on the mobility of the agent, it might be static or dynamic. The needed sensors and behaviors of the Agent will also alter in response to a slight change in the surroundings.
Actuators − Agents rely on actuators to function in their surroundings. Display boards, object-picking arms, track-changing devices, etc. are examples of actuators. The environment can alter as a result of actions taken by agents.
Sensors − By providing agents with a comprehensive collection of Inputs, sensors enable them to comprehend their surroundings. Agent behavior is influenced by their recent past and their present input set. Various sensing devices, such as cameras, GPS, odometers, and others, are examples of sensors.
Examples of PEAS Descriptors
1. PEAS Descriptor of Automated Car Driver
Safety − The automated system needs to be able to operate the vehicle securely without rushing.
Optimized Speed − Depending on the environment, automated systems should be able to maintain the ideal speed.
Journey − The end-user should have a comfortable journey thanks to automated systems.
Roads − Automated automobile drivers ought to be able to go on any type of route, from local streets to interstates.
Traffic Conditions − For various types of roadways, there are various traffic conditions to be found.
Steering wheel − to point an automobile in the appropriate direction.
Gears and accelerators − adjusting the car's speed up or down.
In-car driving tools like cameras, sonar systems, etc. are used to collect environmental data.
2. PEAS Descriptor of Disputter
Performance − Efficiency, safety (doesn't collide with any people), battery life, recall (collects all the dirty dishes), accuracy (only collects dirty dishes), damage control (doesn't damage any kitchen equipment), and recall (collects only dirty dishes)
Environment − a space, a sink, a counter, a stove, a dishwasher, several dish kinds, dishwashing soap, people, a potentially spill-prone floor, and a counter
Actuators − Wheels, cushioned claws, a music speaker, a battery
Sensors − Lasers to assess room layout and any moving objects to prevent collisions, vision sensors (for dish type, position, degree of grime, and dishwasher "fullness"), and a texture sensor for the floor to detect spills.
PEAS is fantastic as a first step to comprehending the task your agent is given while fixing an issue. Performance, Environment, Actuators, and Sensors are together known as PEAS. For an intelligent agent, they aid in defining the job environment. Consequently, PEAS is a crucial representation system for creating an AI model.
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