Lecture Details
Days: FridayDuration: 1:30 PM - 4:15 PM (Aug 18 - Dec 01)
Lecture Hall: Lattie Coor Hall 174 (Tempe)
Submissions: Canvas
Syllabus: Course Syllabus
Live Lecture: Zoom Link provided in Canvas
Contact info: atricham@asu...
Description
This course offers a comprehensive exploration of planning and learning methods in Artificial Intelligence (AI). Students will gain a deep understanding of how AI systems can make informed decisions, strategize effectively, and adapt in dynamic environments. The course covers both theoretical foundations and practical applications of planning and learning algorithms, empowering students with the skills to design intelligent systems capable of autonomous decision-making. Topics include reasoning about time and action, plan synthesis and execution, sequential decision support, and reinforcement learning.Prerequisites :
It is highly recommended that students complete CSE 471: Introduction to AI or CSE 475: Foundations of Machine Learning in order to be successful in this course.Course Schedule:
WEEK | LECTURE | IMPORTANT DATES | NOTES |
---|---|---|---|
Week 1 08/18/2023 |
Intro to decision-making | Week 1 Lecture | |
Week 2 08/25/2023 |
Myopic planning Pytorch Tutorial |
Week 2 Lecture Pytorch Tutorial Additional Reading : Algorithms for Optimization:Section 15, Section 16 |
|
Week 3 09/01/2023 |
Myopic planning Robot Planning tutorial |
Week 3 Lecture ROS Tutorial |
|
Week 4 09/08/2023 |
Non-myopic planning and reinforcement learning | Assignment 1 released: 6th Sept | Assignment 1 code files Week 4 Lecture Assignment 1 Part A solutions |
Week 5 09/15/2023 |
Non-myopic planning and reinforcement learning | Week 5 Lecture Additional Reading : SayCan |
|
Week 6 09/22/2023 |
Imitation learning for decision-making | Assignment 1 Due Date: 19th Sept Assignment 2 released: 20th Sept |
Week 6 Lecture Assignment 2 Guidelines |
Week 7 09/29/2023 |
Imitation learning for decision-making | Project team formation and idea Due date: 25th Sept Project Proposal Presentation : 29th Sept |
Week 7 Lecture Project Guidelines Project Report Template |
Week 8 10/06/2023 |
Human-in-the-loop planning | Week 8 Lecture Additional Reading : InstructGPT |
|
Week 9 10/13/2023 |
Human-in-the-loop planning | Assignment 2 Part 1: Due on 13th Oct Assignment 2 Part 2: Due on 15th Oct |
Week 9 Lecture Student Presentations- RL algorithms |
Week 10 10/20/2023 |
Task and Motion planning | Week 10 Lecture | |
Week 11 10/27/2023 |
Task and Motion planning | Project Progress Presentation : 27th Oct | |
Week 12 11/03/2023 |
Multiagent planning and decision-making under uncertainty | ||
Week 13 11/10/2023 |
Veterans Day Observed (Classes excused/University closed) |
||
Week 14 11/17/2023 |
Classical planning and hierarchical planning/learning | Assignment 3 released: 12th Nov | |
Week 15 11/24/2023 |
Thanksgiving Holiday Observed (Classes excused/University closed) |
Assignment 3 Due Date: 27th Nov | |
Week 16 12/01/2023 |
Project presentations | Final Project Presentations : 1st Dec Final Project Report : 3rd Dec |
Project Guidelines |
Textbook & Additional Reading :
Algorithms for Decision MakingAlgorithms for Optimization
Artificial Intelligence: A Modern Approach (4th US edition)
Reinforcement Learning: An Introduction (2nd edition)
Teaching Team :
E-mail: ywan1053@asu...
Office hours: Wed, 2:00 PM - 3:00 PM
Virtual: Meeting Link
Office: BYENG 211
Office hours: Wed, 2:00 PM - 3:00 PM
Virtual: Meeting Link
Office: BYENG 211
E-mail: nkondepu@asu...
Office hours: Ad-hoc (post grading)
Office hours: Ad-hoc (post grading)
E-mail: hmankodi@asu...
Office hours: Ad-hoc (post grading)
Office hours: Ad-hoc (post grading)