cs 531/331: introduction to ai

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CS 331: Dr M M Awais (LUMS) CS 531/331: Introduction to AI Mian Muhammad Awais Room 416 [email protected]

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CS 531/331: Introduction to AI. Mian Muhammad Awais Room 416 [email protected]. Course Description. Course home page : suraj/lums.edu.pk/~cs331a05 Contacts :lecture notes, tutorials, assignment, grading, office hours, etc. Textbooks: - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

CS 531/331: Introduction to AI

Mian Muhammad Awais

Room 416

[email protected]

Page 2: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Course DescriptionCourse home page: suraj/lums.edu.pk/~cs331a05Contacts:lecture notes, tutorials, assignment, grading, office hours, etc.Textbooks: 1) Luger: Artificial Intelligence: Structures and Strategies for Complex Problem-solving Fourth Edition (Available as Reading package)2) S. Russell and P. Norvig Artificial Intelligence: A Modern Approach Prentice Hall, 2003, First or Second Edition (HANDOUTS)Grading:

Quizzes (15%)Lab/Assignments/Project (15%), Midterm test (30%)Final exam (40%)

At least 2 Lab Assignments where attendance will be compulsory and will be taken. Midterm test (in class) and final exam (as per schedule)

Page 3: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

TA Support/Office Hours

• Natasha Qureshi (TA)

[email protected]

Office hours (see the website)

• Instructor Office Hours:

3 to 4 PM Every day except Friday

Page 4: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Course Outline

• Introduction and Problem Solving (Today’s Lecture)

• Part I:Knowledge Representation

• Part II:Informed Search Methods

• Part III:Planning / Reasoning/Expert Systems

• Part IV:Learning

Page 5: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Book Chapters

• Book Chapters and articles will be announced as we go along

• Slides will be available at the website and the common’s folder

Page 6: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Informal Feedback Mechanism

• Every Two Weeks an anonymous questionnaire will be circulated to evaluate the course

• Your comments will be welcomed to improve the course

• We will also have course progress discussion after every two weeks

Page 7: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Questions

Page 8: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

AI Dimensions

1) Modeling: Thought process/reasoning vs. behavior/action

2) Evaluation: Success according to human standards vs. success according to an ideal concept of intelligence: rationality.

Page 9: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

What is AI?

Views of AI fall into four categories:

Thinking humanly Thinking rationally

Acting humanly Acting rationally

Our Focus is "ACTING RATIONALLY"

Page 10: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

"Can machines behave like Humans?"

Acting humanly: Meaning

Page 11: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Acting humanly: Turing Test

• Turing (1950) "Computing machinery and intelligence":• Operational test for intelligent behavior: the Imitation Game

• Predicted that by 2000, a machine might have a 30% chance of fooling a lay person for 5 minutes

• Anticipated all major arguments against AI in following 50 years• Suggested major components of AI: knowledge, reasoning, language

understanding, learning

••

Page 12: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Page 13: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Objections :- Turning Test

Most AI Programs Are Not Flexible In Nature

May Not Be Able to Answer Emotional Questions

Page 14: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Thinking humanly

“Can machines think like humans”

• Requires scientific theories of internal activities of the brain

• Cognitive Modeling

Page 15: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Thinking humanly: cognitive modeling

•1960s "cognitive revolution": information-processing psychology

•Validation Requires

•Predicting and testing behavior of human subjects (top-down)

•Direct identification from neurological data (bottom-up)

•Cognitive Science and Cognitive Neuroscience

•Distinct from AI

Page 16: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Thinking humanly: Some References

– Daniel C. Dennet. Consciousness explained.– M. Posner (edt.) Foundations of cognitive science– Francisco J. Varela et al. The Embodied Mind– J.-P. Dupuy. The mechanization of the mind

Page 17: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Thinking rationally

“Laws of Thought”

“Can machines think rationally”

Several Greek schools developed various forms of logic: notation and rules of derivation for thoughts; may or may not have proceeded to the idea of mechanization

Page 18: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Aristotle: what are correct arguments/thought processes?

Mathematics and Philosophy to Modern AI

Problems: 1. Not all intelligent behavior is mediated by logical

deliberation2. What is the purpose of thinking? What thoughts should I

have?

A reference; Ivan Bratko, Prolog programming for artificial intelligence.

Thinking rationally

Page 19: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Acting rationally

“Can machines behave rationally”

• Rational behavior: doing the right thing• The right thing: that which is expected to

maximize goal achievement, given the available information

• Doesn't necessarily involve thinking – e.g., blinking reflex – but thinking should be in the service of rational action

Page 20: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Rational Agents

• An agent is an entity that perceives and acts• Every thing to be discussed should be taken in the

context of :RATIONAL AGENTS

• Abstractly, an agent is a function from percept histories to actions:

[f: P* A]• For a given class of environments/tasks, Rational

Agents sought best performance

Page 21: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Computational limitations make perfect rationality unachievable

(this leads to)

Design best program for given machine resources

Limitations:Rational Agents

References

Michael Wooldridge. Reasoning about rational agents.

Page 22: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Definition: AI Systems

Artificial Systems that behave rationally

Page 23: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Another Definition: AI?

Computer based solution of complex problems through the application of processes that are analogous to the

Human Intelligence

CONTROVERSIAL ISSUE

(How to define Intelligence)

More inclined towards acting and thinking humanly

Page 24: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

IntelligenceReasoning + Learning

Intelligent Beings

Intelligent Systems

- Establishes Relationships- Perception and Comprehension- Generalization Ability

- Memory/Differentiation Chair vs Table Spoon vs Fork

Page 25: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

AI Though Groups

Strong Believers

Weak Believers

Page 26: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Weak AI?

Computation Consciousness

Brain has ingredients that are

Non - computational

Simulating consciousness is not possible

Computational + Non Computational

BRAIN

Page 27: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Strong AI ?

Consciousness - “is some complicated computation”

Brains Are Computers of MEAT?

“Computers can achieve or even exceed all Human Capacities once high computational speeds are achieved”

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CS 331: Dr M M Awais (LUMS)

Scope of AI Based Techniques

Main focus Problems that do not have algorithmic solutions, or are very complex

Vague, uncertain and poor-defined systems

Systems with decision - making problems

(Examples?)

Page 29: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Example Tasks

Game Playing Rules are well defined algorithmic solutions are very complex Formalization is easy

Automated Reasoning Theorem proving Formal logic/ knowledge representation.

Expert SystemsMimic experts such as doctors

Coding

Knowledge Diagnostic

Experts

Experts

Page 30: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Natural Language Processing

Computer learn human languages Machine Translation Speech Synthesis

Planning And Robotics Artificial Pets. Efforts to make “machines”

- Responsive

- Flexible

e.g., Path Planning

Human Machine

Page 31: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Summary: AI?

• Innovative Extension of Philosophy:– Understand and BUILD intelligent entities

• Formal Origin after WWII

• Highly interdisciplinary

• Variety of subfields– This course will discuss some of them

Page 32: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

AI prehistory

• Philosophy Logic, methods of reasoning, mind as physical system foundations of learning, language,

rationality• Mathematics Formal representation and proof algorithms,

computation, (un)decidability, (in)tractability,probability

• Economics Utility, decision theory • Neuroscience Physical substrate for mental activity• Psychology Phenomena of perception and motor control,

experimental techniques• Computer Building fast computers

engineering• Control theory Design systems that maximize an objective

function over time • Linguistics Knowledge representation, grammar

Page 33: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

History of AI

• 1943 McCulloch & Pitts: Boolean circuit model of brain• 1950 Turing's "Computing Machinery and Intelligence"• 1956 Dartmouth meeting: "Artificial Intelligence" adopted• 1952—69 Look, Ma, no hands! • 1950s Early AI programs, including Samuel's checkers

program, Newell & Simon's Logic Theorist, Gelernter's Geometry Engine

• 1965 Robinson's complete algorithm for logical reasoning• 1966—73 AI discovers computational complexity

Neural network research almost disappears• 1969—79 Early development of knowledge-based systems• 1980-- AI becomes an industry • 1986-- Neural networks return to popularity• 1987-- AI becomes a science • 1995-- The emergence of intelligent agents

Page 34: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

State of the art AI

• Deep Blue defeated the reigning world chess champion Garry Kasparov in 1997

• Proved a mathematical conjecture (Robbins conjecture) unsolved for decades

• No hands across America (driving autonomously 98% of the time from Pittsburgh to San Diego)

• During the 1991 Gulf War, US forces deployed an AI logistics planning and scheduling program that involved up to 50,000 vehicles, cargo, and people

• NASA's on-board autonomous planning program controlled the scheduling of operations for a spacecraft

• Proverb solves crossword puzzles better than most humans

Page 35: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

First Reading Assignment(Write a Two Page Summary on the Scope of AI)

Submission: Email the article to Instructor /TA by Friday 5:00 pm

1. Luger’s

Chapter One: Introduction

Other References:

Alexander Igor’s Impossible minds

(Help Material Available in the Library)

Page 36: CS 531/331: Introduction to AI

CS 331: Dr M M Awais (LUMS)

Topics Covered Today

• Luger (Some of the discussion is from Stuart and Norvig)

– Part I– Chapter 1– Articles 1.1 to 1.4

• Practice:– Attempt Exercise Questions– Especially: Qs 1 to 7, 10 to 12