Artificial Intelligence PEAS
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The document discusses the PEAS framework for describing an agent's task environment. PEAS stands for Performance measure, Environment, Actuators, and Sensors. It provides examples of applying PEAS to describe the environments of a taxi driver, part-picking robot, medical diagnosis system, and interactive English tutor. For each, it lists the relevant performance measure, environment, actuators, and sensors.
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The document defines key concepts in artificial intelligence including intelligent agents, environments, and rational agents. An intelligent agent is anything that can perceive its environment and take actions to achieve its goals. Rational agents aim to maximize their performance measure given their percepts and knowledge. Different types of agents are described including reflex agents, model-based agents, goal-based agents, and utility-based agents. State representations and learning agents are also covered at a high level.
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n artificial intelligence, an intelligent agent (IA) is an autonomous entity which acts, directing its activity towards achieving goals (i.e. it is an agent), upon an environment using observation through sensors and consequent actuators (i.e. it is intelligent).An intelligent agent is a program that can make decisions or perform a service based on its environment, user input and experiences. These programs can be used to autonomously gather information on a regular, programmed schedule or when prompted by the user in real time. Intelligent agents may also be referred to as a bot, which is short for robot.Examples of intelligent agents
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Examples of intelligent agents
AI assistants, like Alexa and Siri, are examples of intelligent agents as they use sensors to perceive a request made by the user and the automatically collect data from the internet without the user's help. They can be used to gather information about its perceived environment such as weather and time.
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1. peas
The document discusses the PEAS framework for defining intelligent agent environments. It provides examples of applying PEAS to autonomous taxis, spam filters, medical diagnosis systems, part-picking robots, and English tutors. It then outlines different types of environments, including fully/partially observable, static/dynamic, discrete/continuous, deterministic/stochastic, single-agent/multi-agent, episodic/sequential, known/unknown, and accessible/inaccessible.
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AI assistants, like Alexa and Siri, are examples of intelligent agents as they use sensors to perceive a request made by the user and the automatically collect data from the internet without the user's help. They can be used to gather information about its perceived environment such as weather and time.
Infogate is another example of an intelligent agent, which alerts users about news based on specified topics of interest.
Autonomous vehicles could also be considered intelligent agents as they use sensors, GPS and cameras to make reactive decisions based on the environment to maneuver through traffic.
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2) It introduces the concept of rational agents and the PEAS framework for defining an agent's Performance measure, Environment, Actuators, and Sensors. Several examples of applying PEAS are described.
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It helps us to decide which rule has to apply next without getting stuck at any point.
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A good Control strategy has two main
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Each rule or strategy applied should cause the motion because if there will be no motion than such control strategy will never lead to a solution. Motion states about the change of state and if a state will not change then there be no movement from an initial state and we would never solve the problem.
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Do not view this online or it will not be compatible Download it to view videos and see original slides :))
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Artificial Intelligence PEAS
- 2. PEAS • Use PEAS to describe task environment – Performance measure – Environment – Actuators – Sensors • Example: Taxi driver – Performance measure: safe, fast, comfortable (maximize profits) – Environment: roads, other traffic, pedestrians, customers – Actuators: steering, accelerator, brake, signal, horn – Sensors: cameras, sonar, speedometer, GPS, odometer, accelerometer, engine sensors
- 3. PEAS • Agent: Part-picking robot • Performance measure: Percentage of parts in correct bins • Environment: Conveyor belt with parts, bins • Actuators: Jointed arm and hand • Sensors: Camera, joint angle sensors
- 4. PEAS • Agent: Medical diagnosis system • Performance measure: Healthy patient, minimize costs, lawsuits • Environment: Patient, hospital, staff • Actuators: Screen display (questions, tests, diagnoses, treatments, referrals) • • Sensors: Keyboard (entry of symptoms, findings, patient's answers)
- 5. PEAS • Agent: Interactive English tutor • Performance measure: Maximize student's score on test • Environment: Set of students • Actuators: Screen display (exercises, suggestions, corrections) • Sensors: Keyboard