C0: Introduction

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Most materials in this chapter are based on materials from https://ai.berkeley.edu
C0
Introduction
COMP3270
Introduction to Artificial Intelligence

What Would Count as Intelligence?

What Would Count as Intelligence?
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TASK
ACalculator
BChess Engine
CChatbot
DSelf-Driving Car
What evidence are you using?

How Should We Judge Intelligence?

How Should We Judge Intelligence?
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What do we evaluate?
THINKING ACTING
What is the benchmark?
HUMAN-LIKE RATIONAL
Combine the answers → four ways to define AI

Build AI That…

Build AI That…
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Which Approach Guides Each AI System?

Which Approach Guides Each AI System?
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TASK
AI System
Approach
A hypothetical brain simulation that reproduces how humans think
A chatbot designed to convince a judge that it is human
An automated theorem prover that derives valid conclusions
A self-driving car that chooses actions to reach its destination safely

Thinking Humanly Models Human Cognition

Thinking Humanly Models Human Cognition
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TASK
OBSERVE Human Thinking Introspection · experiments · brain activity
→
MODEL Computational Process Turn a theory into a program
→
COMPARE Model and People Do they solve the task in the same way?
A person and a model give the same answer. Does that mean they thought in the same way?

Acting Humanly Tests Human-Like Behaviour

Acting Humanly Tests Human-Like Behaviour
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Can a judge reliably tell which response came from a person?
The test evaluates observable behaviour, not the hidden process

Thinking Rationally Applies Correct Reasoning

Thinking Rationally Applies Correct Reasoning
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TASK
All men are mortal
Socrates is a man
Therefore, Socrates is mortal
What is the limitation of this approach?

This Course Focuses on Acting Rationally

This Course Focuses on Acting Rationally
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DEFINITION
Choose the action expected to achieve the best outcome

Example: Acting Rationally Under Uncertainty

Example: Acting Rationally Under Uncertainty
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TASK
FORECAST 70% chance of rain
→
ACTION ☂ take an umbrella
→
OUTCOME ☀ it stays dry
Was taking the umbrella irrational?

An Agent Perceives, Decides, and Acts

An Agent Perceives, Decides, and Acts
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An agent is anything that perceives its environment and acts upon it.
ENVIRONMENT percepts AGENT actions
The loop repeats as the world changes

What Made This Choice Rational?

What Made This Choice Rational?
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Taking the umbrella depended on four things
OBJECTIVEStay dry
EVIDENCE70% chance of rain
KNOWLEDGEAn umbrella reduces the risk
ACTIONSTake it or leave it

Rational Does Not Mean Omniscient

Rational Does Not Mean Omniscient
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RATIONAL ≠ KNOWS THE FUTURE
Use the information available now
Choose under limited time and memory
A rational decision can still lead to a bad outcome

A Self-Driving Car With One Objective

A Self-Driving Car With One Objective
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TASK
SELF-DRIVING CARMaximize safety
DESTINATION
Which behaviour receives the highest score?

A Vacuum Robot With One Objective

A Vacuum Robot With One Objective
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TASK
VACUUM-CLEANING ROBOTCollect as much dirt as possible
ROBOT
How could the robot maximize its score?

Specify the Performance Measure Carefully

Specify the Performance Measure Carefully
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PERFORMANCE MEASURE How the agent's success is scored
POOR MEASUREAmount of dirt collected
BETTER MEASURECleanliness maintained over time
ALSO CONSIDERcoverage · energy · time · safety

This Course Builds a Toolkit for Rational Action

This Course Builds a Toolkit for Rational Action
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SEARCH · C1Which action sequence reaches the goal?
MDPs · C2Which action is best when outcomes are uncertain?
REINFORCEMENT LEARNING · C3How can an agent improve from experience?
PROBABILISTIC MODELS · C4–C6What should the agent believe from noisy evidence?
LOGIC · C7What follows from what the agent knows?

AI Progress Comes in Waves

AI Progress Comes in Waves
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1950sLogic and Search
1970s–80sExpert Systems
1990s–2000sProbability and Data
2010sDeep Learning
2020sGenerative and Agentic AI
Each wave solves some problems and reveals new limitations

The Thinking Machine, 1961

The Thinking Machine, 1961
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TASK
What stands out about the way they describe intelligent machines?

Reference Materials

Reference Materials
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Course Details 2-page course guide Course focus, schedule, assessment, and policies AIMA: Chapter 1 66 pages comp3270.dirk.hk/AIMA_Chapter_1.pdf  ·  Password: Schnieders AIMA: Chapter 2 49 pages comp3270.dirk.hk/AIMA_Chapter_2.pdf  ·  Password: Dirk The Thinking Machine: MIT 1961 53-minute film comp3270.dirk.hk/the_thinking_machine_mit_1961.mp4