Agent_Search

Agent_Search - Intelligent Agents and Search Problems...

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Intelligent Agents and Search Problems Chapters 2 & 3
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Outline Intelligent Agents Agents and environments Rationality PEAS (Performance measure, Environment, Actuators, Sensors) Environment types Agent types Search Problems
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Agents An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators 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
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Agents and environments The agent function maps from percept histories to actions: [ f : P* A ] The agent program runs on the physical architecture to produce f agent = architecture + program
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Vacuum-cleaner world Percepts: location and contents, e.g., [A,Dirty] Actions: Left , Right , Suck , NoOp
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A vacuum-cleaner agent
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Rational agents An agent should strive to " do the right thing ", based on what it can perceive and the actions it can perform. The right action is the one that will cause the agent to be most successful Performance measure: An objective criterion for success of an agent's behavior E.g., 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.
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Rational agents Rational Agent : 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.
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PEAS PEAS: Performance measure, Environment, Actuators, Sensors Must first specify the setting for intelligent agent design Consider, e.g., the task of designing an automated taxi driver: Performance measure Environment Actuators Sensors
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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
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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)
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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
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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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This note was uploaded on 11/15/2011 for the course CAP 4630 taught by Professor Staff during the Fall '08 term at FAU.

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Agent_Search - Intelligent Agents and Search Problems...

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