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Intelligent Agents

Intelligent Agents. Chapter 2. Outline of this lecture. Agents and environments Rationality PEAS (Performance measure, Environment, Actuators, Sensors) Environment types Agent types. Agents.

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Intelligent Agents

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  1. Intelligent Agents Chapter 2

  2. Outline of this lecture • Agents and environments • Rationality • PEAS (Performance measure, Environment, Actuators, Sensors) • Environment types • Agent types

  3. Agents • Anagentis anything that can be viewed asperceivingitsenvironmentthroughsensorsandactingupon that environment throughactuators • Human agent: eyes, ears, and other organs for sensors; hands, legs, mouth, and other body parts for actuators • Robotic agent: cameras and infrared range finders for sensors; various motors for actuators

  4. Terminology • Percept: The agents perceptual input at a given instant. • Percept sequence: Complete history of everything that the agent has perceived. An agents action can depend on this. • Agent function(Abstract mathematical description):An external characterization that describes an agents behaviour by mapping any given percept sequence to an action. This can be an infinite table unless we limit the length of the sequence. • Agent program: Internal representation that implements the agent and runs on the agent architecture.

  5. Agents and environments • Theagentfunctionmaps from percept histories to actions: [f: P* A] • Theagentprogramruns on the physicalarchitectureto produce f • agent = architecture + program

  6. A simple exampleVacuum-cleaner world • Percepts:location and contents, e.g., [A,Dirty] • two locations: squares A & B • Actions: Left,Right, Suck, NoOp

  7. Partial tabulation ofthe vacuum-cleaner agent A calculator can be thought of as an agent. Given the percept sequence 2+2= chooses the action of displaying 4

  8. Rational agents • The right action is the one that will cause the agent to be most successful. How do we measure success? • Performance measure: An objective criterion for success of an agent's behavior. • Performance measure of a vacuum-cleaner agent could be amount of dirt cleaned up, amount of time taken, amount of electricity consumed, amount of noise generated, etc.

  9. Rational Agents • RationalAgent: For each possible percept sequence, a rational agent should select an action that is expected to maximize its performance measure, given the evidence provided by the percept sequence and whatever built-in knowledge the agent has.

  10. Rational agents • Rationality is distinct from omniscience (all-knowing with infinite knowledge): Is Crossing the street to meet an old friend rational? • Rational agent: For each possible percept an action that maximizes the performance measure. Rationality is not the same as perfection. • An agent isautonomousif its behavior is determined by its own experience (with ability to learn and adapt) as opposed to prior knowledge of its designer.

  11. Task EnvironmentPEAS • PEAS: Performance measure, Environment, Actuators, Sensors • First step in intelligent agent design: specify the task environment as fully as possible • Consider, e.g., the task of designing an automated taxi driver(Beyond the capabilities of the current technology): • Performance measure • Environment • Actuators • Sensors

  12. PEAS • Must first specify the setting for intelligent agent design • Consider, e.g., the task of designing an automated taxi driver: • Performance measure: Safe, fast, legal, comfortable trip, maximize profits • Environment: Roads, other traffic, pedestrians, customers • Actuators: Steering wheel, accelerator, brake, signal, horn • Sensors: Cameras, sonar, speedometer, GPS, odometer, engine sensors, keyboard

  13. PEAS • Agent: Medical diagnosis system (MYCIN) • 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)

  14. 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

  15. 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

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