DOC PREVIEW
UNCC ITCS 3153 - Lecture Notes

This preview shows page 1-2-3-25-26-27 out of 27 pages.

Save
View full document
View full document
Premium Document
Do you want full access? Go Premium and unlock all 27 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 27 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 27 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 27 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 27 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 27 pages.
Access to all documents
Download any document
Ad free experience
Premium Document
Do you want full access? Go Premium and unlock all 27 pages.
Access to all documents
Download any document
Ad free experience

Unformatted text preview:

ITCS 3153 Artificial IntelligenceChess ArticleSlide 3What is an agent?PerceptionAn agent as a functionEvaluating agent programsRational AgentLearning and AutonomyAdding intelligence to agent functionHow big is your percept?Qualities of a task environmentSlide 13Slide 14Slide 15Slide 16Slide 17Building Agent ProgramsSimple Reflex AgentsSlide 20Model-based Reflex AgentsSlide 22Goal-based AgentsUtility-based AgentsLearning AgentsA taxi driverReviewITCS 3153Artificial IntelligenceLecture 2Lecture 2AgentsAgentsLecture 2Lecture 2AgentsAgentsChess ArticleDeep Blue (IBM)Deep Blue (IBM)•418 processors, 200 million positions per second418 processors, 200 million positions per secondDeep Junior (Israeli Co.)Deep Junior (Israeli Co.)•8 processors, 3 million positions per second8 processors, 3 million positions per secondKasparovKasparov•100 billion neurons in brain, 2 moves per second100 billion neurons in brain, 2 moves per secondBut there are 85 billion ways to play the first four movesBut there are 85 billion ways to play the first four movesDeep Blue (IBM)Deep Blue (IBM)•418 processors, 200 million positions per second418 processors, 200 million positions per secondDeep Junior (Israeli Co.)Deep Junior (Israeli Co.)•8 processors, 3 million positions per second8 processors, 3 million positions per secondKasparovKasparov•100 billion neurons in brain, 2 moves per second100 billion neurons in brain, 2 moves per secondBut there are 85 billion ways to play the first four movesBut there are 85 billion ways to play the first four movesChess ArticleCognitive psychologists report chess is a game of Cognitive psychologists report chess is a game of pattern matching for humanspattern matching for humans•But what patterns do we see?But what patterns do we see?•What rules do we use to evaluate perceived patterns?What rules do we use to evaluate perceived patterns?Cognitive psychologists report chess is a game of Cognitive psychologists report chess is a game of pattern matching for humanspattern matching for humans•But what patterns do we see?But what patterns do we see?•What rules do we use to evaluate perceived patterns?What rules do we use to evaluate perceived patterns?What is an agent?PerceptionPerception•Sensors receive input from environmentSensors receive input from environment–Keyboard clicksKeyboard clicks–Camera dataCamera data–Bump sensorBump sensorActionAction•Actuators impact the environmentActuators impact the environment–Move a robotic armMove a robotic arm–Generate output for computer displayGenerate output for computer displayPerceptionPerception•Sensors receive input from environmentSensors receive input from environment–Keyboard clicksKeyboard clicks–Camera dataCamera data–Bump sensorBump sensorActionAction•Actuators impact the environmentActuators impact the environment–Move a robotic armMove a robotic arm–Generate output for computer displayGenerate output for computer displayPerceptionPerceptPercept•Perceptual inputs at an instantPerceptual inputs at an instant•May include perception of internal stateMay include perception of internal statePercept SequencePercept Sequence•Complete history of all prior perceptsComplete history of all prior perceptsDo you need a Do you need a percept sequencepercept sequence to play Chess? to play Chess?PerceptPercept•Perceptual inputs at an instantPerceptual inputs at an instant•May include perception of internal stateMay include perception of internal statePercept SequencePercept Sequence•Complete history of all prior perceptsComplete history of all prior perceptsDo you need a Do you need a percept sequencepercept sequence to play Chess? to play Chess?An agent as a functionAgent maps percept sequence to actionAgent maps percept sequence to action•Agent:Agent:–Set of all inputs known as Set of all inputs known as state spacestate spaceAgent FunctionAgent Function•If inputs are finite, a table can store mappingIf inputs are finite, a table can store mapping•Scalable?Scalable?•Reverse Engineering?Reverse Engineering?Agent maps percept sequence to actionAgent maps percept sequence to action•Agent:Agent:–Set of all inputs known as Set of all inputs known as state spacestate spaceAgent FunctionAgent Function•If inputs are finite, a table can store mappingIf inputs are finite, a table can store mapping•Scalable?Scalable?•Reverse Engineering?Reverse Engineering?*;)( ppsapsf Evaluating agent programsWe agree on what an agent must doWe agree on what an agent must doCan we evaluate its quality?Can we evaluate its quality?Performance MetricsPerformance Metrics•Very ImportantVery Important•Frequently the hardest part of the research problemFrequently the hardest part of the research problem•Design these to suit what you really want to happenDesign these to suit what you really want to happenWe agree on what an agent must doWe agree on what an agent must doCan we evaluate its quality?Can we evaluate its quality?Performance MetricsPerformance Metrics•Very ImportantVery Important•Frequently the hardest part of the research problemFrequently the hardest part of the research problem•Design these to suit what you really want to happenDesign these to suit what you really want to happenRational AgentFor each percept sequence, a rational agent For each percept sequence, a rational agent should select an action that maximizes its should select an action that maximizes its performance measureperformance measureExample: autonomous vacuum cleanerExample: autonomous vacuum cleaner•What is the performance measure?What is the performance measure?For each percept sequence, a rational agent For each percept sequence, a rational agent should select an action that maximizes its should select an action that maximizes its performance measureperformance measureExample: autonomous vacuum cleanerExample: autonomous vacuum cleaner•What is the performance measure?What is the performance measure?•Penalty for eating the cat? How much?Penalty for eating the cat? How much?•Penalty for missing a spot?Penalty for missing a spot?•Reward for speed?Reward for speed?•Reward for conserving power?Reward for conserving power?•Penalty for eating the cat? How much?Penalty for eating the cat? How much?•Penalty for missing a spot?Penalty for missing a spot?•Reward for speed?Reward for speed?•Reward for conserving power?Reward for conserving power?Learning and


View Full Document

UNCC ITCS 3153 - Lecture Notes

Download Lecture Notes
Our administrator received your request to download this document. We will send you the file to your email shortly.
Loading Unlocking...
Login

Join to view Lecture Notes and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view Lecture Notes 2 2 and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?