LOGISTICS
Course website:
venkat.prof/CS4100
24/7 Discussion Forum:
Campuswire
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Components
Assignment 0 + 2 Labs (10%)
3 Problem Sets (20%)
3 Programming Assignments (30%)
Group Final Project* (40%)
(presentation, final report, modular code in GitHub repo)
* can be swapped out for a research-intensive pathway (harder)
Attendance Requirements
Mandatory attendance - project presentations, last 3 lectures
Must be present even if you're not presenting on that day
No remote options for any lectures
Policies - Homework Submissions
Deadlines: 6:00 pm, Friday
Assignments will be released on Canvas
Submissions: Gradescope
Grades released on Gradescope
Regrade Requests: submit within 1 week of receiving grade
Late Policy
Automatic extension until Sunday 6:00 pm
Warning: No office hours during this period
Does not apply to project submissions, labs or presentations
If you have accommodations through DAS, get the notification letter sent ASAP
Life happens, come talk to me!
Policy on Collaboration and Generative AI
Discussing concepts is okay.
Discussing the actual problem on the assignment is not.
If in doubt, just ask me!
For programming assignments (except assignment 0), use whatever you'd like, but cite it.
For problem sets, the use of generative AI is prohibited.*
*If you use gen AI only to rephrase for writing clarity,
you must submit an appendix with your original answers.
Course Rigor
This is not an easy course.
AI is inherently complex and mathematical.
There will be equations, lots of them.
Most students who work hard get an A.
This is not because I'm lenient - they had to earn it.
Academic Integrity
If I catch you cheating...
- You will fail this course
- You will be reported to OSCCR
Penalties ranging from warnings/probation to dismissal
My Expectations From You
Come to class having studied notes in advance
Manage your time wisely - you will always have conflicting deadlines
Read all instructions, follow policies strictly, and do not cheat!
Come to office hours - get to know me outside class
Challenge yourselves - that's why you're here!
Ask questions - I'm here to help you learn!
My Commitments To You
I will always welcome student questions
I will foster a nonjudgmental environment
You can reach out to me for any reason*
*Faculty are mandatory reporters at Northeastern - see syllabus for details.
Required Background
Python 3, strong programming skills
Basics of Linear Algebra
(matrix and vector operations, dot products)
Basics of Probability & Statistics
(conditional probability, Bayes' theorem)
Basics of Calculus
(differentiation, partial derivatives)
Assignment 0 - out today!
Self-placement/evaluation
Locked until Syllabus Quiz is completed
Covers required background
Tests programming ability
Contains resources to build necessary skills
Due on Sep 12
Attempt this honestly - I don't expect anyone to know everything!
Any questions for/about me?
Can Machines Think?
Alan Turing, 1950
Some Philosophical Questions...
Is a machine intelligent if it merely mimics human thinking?
Is a machine intelligent if it can fool a human into believing so?
Could you construct a machine whose workings you couldn't explain?
What does intelligence have to do with free will?
Thinking = symbol manipulation
"Intelligence can be replicated
using a computer program"
- Mathematicians in the 1950s
1956, Dartmouth College, workshop on AI
"The conjecture that every aspect of learning or any other feature of intelligence can be,
in principle, so precisely described that a machine can be made to simulate it"
What is an intelligent agent?
A system or program
that perceives and interacts with its environment
while making informed decisions
to achieve a certain goal or maximize some utility
A system or program
that perceives and interacts with its environment
while making informed decisions
to achieve a certain goal or maximize some utility
How does a program perceive its environment?
- Computer Vision
- Depth Sensors
- Language
- Explicit Representations
A system or program
that perceives and interacts with its environment
while making informed decisions
to achieve a certain goal or maximize some utility
How does a program interact with its environment?
- Physical Interactions
- Image Generation
- Language
A system or program
that perceives and interacts with its environment
while making informed decisions
to achieve a certain goal or maximize some utility
How does a program learn?
- Rule Based Systems
- Learning from Computation
- Learning from Data
- Learning from Mistakes
A system or program
that perceives and interacts with its environment
while making informed decisions
to achieve a certain goal or maximize some utility
How does a program reason?
- Objective Functions
- Utility
- Fairness
- Biases
Consider a Roomba (a robot vacuum)
Think about
- Percepts
- Interactions
- Learning/Inference
- Rationality
How about Netflix/Youtube/Amazon Recommendations?
Think about
- Percepts
- Interactions
- Learning/Inference
- Rationality
Categorizing AI Environments
- Fully Observable v/s Partially Observable
- Single Agent v/s Multi Agent
- Deterministic v/s Non-Deterministic
- Episodic v/s Sequential
- Static v/s Dynamic
- Discrete v/s Continuous
- Known v/s Unknown
Let's now think about building an AI
Consider the Missionaries and Cannibals game...
Consider the Missionaries and Cannibals game...
Representation: State Space Graph
Nodes: States or World Configurations
Edges: Actions
Edge Weights: Cost of Action
Successor/Transition Function: Set of Edges & Edge Weights
Path: Sequence of Actions
Solution: A Path leading from Start to Goal
SEARCH
Assume a Fully Observable, Static, Deterministic, Known environment (for now)
Let us try and formalize the following problems.
Route Planning
- State Space
- Start & End State
- Successor/Transition Function (Action & Cost)
- When riding the T?
- When driving?
Maze Solving
- State Space
- Start & End State
- Successor/Transition Function (Action & Cost)
8 Puzzle
- State Space
- How many possible states?
- Start & End State
- Successor/Transition Function (Action & Cost)
Chess
- State Space
- How many possible states?
- Start & End State
- Successor/Transition Function (Action & Cost)