CS440/ECE448: Artificial Intelligence

Slides:



Advertisements
Similar presentations
Artificial Intelligence
Advertisements

CSCI-100 Introduction to Computing Artificial Intelligence.
Jimma University,JiT Depatment of Computing Introduction To Artificial Intelligence Zelalem H.
Artificial Intelligence
AI 授課教師:顏士淨 2013/09/12 1. Part I & Part II 2  Part I Artificial Intelligence 1 Introduction 2 Intelligent Agents Part II Problem Solving 3 Solving Problems.
What is Artificial Intelligence? –Depends on your perspective... Philosophical: a method for modeling intelligence Psychological: a method for studying.
COMP 590: Artificial Intelligence. Today Course overview What is AI? Examples of AI today.
ICS 101 Fall 2011 Introduction to Artificial Intelligence Asst. Prof. Lipyeow Lim Information & Computer Science Department University of Hawaii at Manoa.
COMP 590: Artificial Intelligence
CS 357 – Intro to Artificial Intelligence  Learn about AI, search techniques, planning, optimization of choice, logic, Bayesian probability theory, learning,
Acting Humanly: The Turing test (1950) “Computing machinery and intelligence”:   Can machine’s think? or Can machines behave intelligently? An operational.
PSU CS 370 – Artificial Intelligence Dr. Mohamed Tounsi Artificial Intelligence 1. Introduction Dr. M. Tounsi.
COMP 3009 Introduction to AI Dr Eleni Mangina
What is Artificial Intelligence? –not programming in LISP or Prolog (!) –depends on your perspective... a method for modeling intelligence a method for.
Introduction to Artificial Intelligence ITK 340, Spring 2010.
ARTIFICIAL INTELLIGENCE Introduction: Chapter Textbook: S. Russell and P. Norvig Artificial Intelligence: A Modern Approach Prentice Hall, 2003,
Artificial Intelligence
CSCE 315: Programming Studio Artificial Intelligence.
Chapter 1 Introduction. General Concepts The field of Artificial Intelligence attempts to understand, model, and simulate the behavior (to some extend)
CPSC 171 Artificial Intelligence Read Chapter 14.
Artificial Intelligence
C463 / B551 Artificial Intelligence Dana Vrajitoru Introduction.
Reference: "Artificial Intelligence, a Modern Approach, 3rd ed."
ARTIFICIAL INTELLIGENCE Introduction: Chapter 1. Outline Course overview What is AI? A brief history The state of the art.
1 AI and Agents CS 171/271 (Chapters 1 and 2) Some text and images in these slides were drawn from Russel & Norvig’s published material.
1 Intelligent Systems Q: Where to start? A: At the beginning (1940) by Denis Riordan Reference Modern Artificial Intelligence began in the middle of the.
Introduction to Artificial Intelligence Artificial Intelligence Section 4 Mr. Sciame.
Introduction: Chapter 1
Artificial Intelligence: Definition “... the branch of computer science that is concerned with the automation of intelligent behavior.” (Luger, 2009) “The.
Artificial Intelligence Lecture No. 3
AI Overview Reference: "Artificial Intelligence, a Modern Approach, 3 rd ed."
Lecture 1 Note: Some slides and/or pictures are adapted from Lecture slides / Books of Dr Zafar Alvi. Text Book - Aritificial Intelligence Illuminated.
ICS 101 Fall 2011 Introduction to Artificial Intelligence Asst. Prof. Lipyeow Lim Information & Computer Science Department University of Hawaii at Manoa.
1 Artificial Intelligence Introduction. 2 What is AI? Various definitions: Building intelligent entities. Getting computers to do tasks which require.
What is Artificial Intelligence? Abbas Mehrabian Teacher: Dr. M. Raei Sharif Saturday, 6 Esfand 1384.
1 CS 2710, ISSP 2610 Foundations of Artificial Intelligence introduction.
Artificial Intelligence: Introduction Department of Computer Science & Engineering Indian Institute of Technology Kharagpur.
Artificial Intelligence
Introduction1 Artificial Intelligence (AI) Introduction Chapter 1.
Exploring Computer Science – Lesson 1-8
Artificial Intelligence IES 503 Asst. Prof. Dr. Senem Kumova Metin.
Introduction to Artificial Intelligence CS 438 Spring 2008 Today –AIMA, Chapter 1 –Defining AI Next Tuesday –Intelligent Agents –AIMA, Chapter 2 –HW: Problem.
Definitions of AI There are as many definitions as there are practitioners. How would you define it? What is important for a system to be intelligent?
University of Kurdistan Artificial Intelligence Methods (AIM) Lecturer: Kaveh Mollazade, Ph.D. Department of Biosystems Engineering, Faculty of Agriculture,
Definitions Think like humansThink rationally Act like humansAct rationally The science of making machines that: This slide deck courtesy of Dan Klein.
What is Artificial Intelligence?
FOUNDATIONS OF ARTIFICIAL INTELLIGENCE
A Brief History of AI Fall 2013 COMP3710 Artificial Intelligence Computing Science Thompson Rivers University.
1 Artificial Intelligence & Prolog Programming CSL 302.
Artificial Intelligence Hossaini Winter Outline book : Artificial intelligence a modern Approach by Stuart Russell, Peter Norvig. A Practical Guide.
AI Overview Reference: "Artificial Intelligence, a Modern Approach, 3 rd ed."
Artificial Intelligence Skepticism by Josh Pippin.
What is Artificial Intelligence? Introduction to Artificial Intelligence Week 2, Semester 1 Jim Smith.
CS440/ECE448: Artificial Intelligence. Section Q course website:
CS440/ECE448: Artificial Intelligence
CS440/ECE448: Artificial Intelligence Lecture 1: What is AI?
Artificial Minds?.
CS4341 Introduction to Artificial Intelligence
Topics Beyond the imitation game Reading the web Turing test
Advanced Artificial Intelligence
Course Instructor: knza ch
Artificial Intelligence (Lecture 1)
Artificial Intelligence Lecture 2: Foundation of Artificial Intelligence By: Nur Uddin, Ph.D.
AI and Agents CS 171/271 (Chapters 1 and 2)
EA C461 – Artificial Intelligence Introduction
COMP3710 Artificial Intelligence Thompson Rivers University
Artificial Intelligence
Artificial Intelligence
Habib Ullah qamar Mscs(se)
Presentation transcript:

CS440/ECE448: Artificial Intelligence

What is AI? Some possible definitions from the textbook: 1. Thinking humanly 2. Acting humanly 3. Thinking rationally 4. Acting rationally

AI definition 1: Thinking humanly Need to study the brain as an information processing machine: cognitive science and neuroscience

AI definition 1: Thinking humanly Can we build a brain? Source: L. Zettlemoyer

AI definition 1: Thinking humanly Can we build a brain? The synapses were randomly connected and the process was meant only to "test the limits of the simulation technology developed in the project and the capabilities of K," RIKEN said in a release.

AI definition 2: Acting humanly The Turing Test What capabilities would a computer need to have to pass the Turing Test? Natural language processing Knowledge representation Automated reasoning Machine learning A. Turing, Computing machinery and intelligence, Mind 59, pp. 433-460, 1950

The Turing Test Turing predicted that by the year 2000, machines would be able to fool 30% of human judges for five minutes Loebner prize 2008 competition: each of 12 judges was given five minutes to conduct simultaneous, split-screen conversations with two hidden entities (human and chatterbot). The winner, Elbot of Artificial Solutions, managed to fool three of the judges into believing it was human [Wikipedia].

Turing Test: Criticism Success depends on deception! Chatbots can do well using “cheap tricks” First example: ELIZA (1966) Chinese room argument: one may simulate intelligence without having true intelligence (more of a philosophical objection)

A better Turing test? http://www.newyorker.com/online/blogs/elements/2013/08/why-cant-my-computer-understand-me.html

H. Levesque, On our best behaviour, IJCAI 2013 A better Turing test? Multiple choice questions that can be easily answered by people but cannot be answered by computers using “cheap tricks”: The trophy would not fit in the brown suitcase because it was so small. What was so small? The trophy The brown suitcase H. Levesque, On our best behaviour, IJCAI 2013

H. Levesque, On our best behaviour, IJCAI 2013 A better Turing test? Multiple choice questions that can be easily answered by people but cannot be answered by computers using “cheap tricks”: The trophy would not fit in the brown suitcase because it was so large. What was so large? The trophy The brown suitcase H. Levesque, On our best behaviour, IJCAI 2013

H. Levesque, On our best behaviour, IJCAI 2013 A better Turing test? Multiple choice questions that can be easily answered by people but cannot be answered by computers using “cheap tricks”: The large ball crashed right through the table because it was made of styrofoam. What was made of styrofoam? The large ball The table H. Levesque, On our best behaviour, IJCAI 2013

H. Levesque, On our best behaviour, IJCAI 2013 A better Turing test? Multiple choice questions that can be easily answered by people but cannot be answered by computers using “cheap tricks”: The large ball crashed right through the table because it was made of steel. What was made of steel? The large ball The table H. Levesque, On our best behaviour, IJCAI 2013

H. Levesque, On our best behaviour, IJCAI 2013 A better Turing test? Multiple choice questions that can be easily answered by people but cannot be answered by computers using “cheap tricks”: The sack of potatoes had been placed below the bag of flour, so it had to be moved first. What had to be moved first? The sack of potatoes The bag of flour H. Levesque, On our best behaviour, IJCAI 2013

H. Levesque, On our best behaviour, IJCAI 2013 A better Turing test? Multiple choice questions that can be easily answered by people but cannot be answered by computers using “cheap tricks”: The sack of potatoes had been placed above the bag of flour, so it had to be moved first. What had to be moved first? The sack of potatoes The bag of flour H. Levesque, On our best behaviour, IJCAI 2013

H. Levesque, On our best behaviour, IJCAI 2013 A better Turing test? Multiple choice questions that can be easily answered by people but cannot be answered by computers using “cheap tricks”: Sam tried to paint a picture of shepherds with sheep, but they ended up looking like golfers. What looked like golfers? The shepherds The sheep H. Levesque, On our best behaviour, IJCAI 2013

H. Levesque, On our best behaviour, IJCAI 2013 A better Turing test? Multiple choice questions that can be easily answered by people but cannot be answered by computers using “cheap tricks”: Sam tried to paint a picture of shepherds with sheep, but they ended up looking like rabbits. What looked like rabbits? The shepherds The sheep H. Levesque, On our best behaviour, IJCAI 2013

H. Levesque, On our best behaviour, IJCAI 2013 A better Turing test? Multiple choice questions that can be easily answered by people but cannot be answered by computers using “cheap tricks”: Sam tried to paint a picture of shepherds with sheep, but they ended up looking like rabbits. What looked like rabbits? The shepherds The sheep H. Levesque, On our best behaviour, IJCAI 2013

H. Levesque, On our best behaviour, IJCAI 2013 A better Turing test? Advantages over standard Turing test Test can be administered and graded by machine Does not depend on human subjectivity Does not require ability to generate English sentences Questions cannot be evaded using verbal dodges Questions can be made “Google-proof” H. Levesque, On our best behaviour, IJCAI 2013

AI definition 3: Thinking rationally Idealized or “right” way of thinking Logic: patterns of argument that always yield correct conclusions when supplied with correct premises “Socrates is a man; all men are mortal; therefore Socrates is mortal.” Logicist approach to AI: describe problem in formal logical notation and apply general deduction procedures to solve it Problems with the logicist approach Computational complexity of finding the solution Describing real-world problems and knowledge in logical notation Dealing with uncertainty A lot of “rational” behavior has nothing to do with logic

AI definition 4: Acting rationally A rational agent acts to optimally achieve its goals Goals are application-dependent and are expressed in terms of the utility of outcomes Being rational means maximizing your (expected) utility This definition of rationality only concerns the decisions/actions that are made, not the cognitive process behind them In practice, utility optimization is subject to the agent’s computational constraints (bounded rationality or bounded optimality)

Utility maximization formulation Advantages Generality: goes beyond explicit reasoning, and even human cognition altogether Practicality: can be adapted to many real-world problems Naturally accommodates uncertainty Amenable to good scientific and engineering methodology Avoids philosophy and psychology Disadvantages? Disadvantages: it may be hard to formulate utility functions. Has limited applicability to humans.