The AI Planning MOOC course materials have been provided in full as an “open-access learning experience which introduces artificial intelligence planning techniques and their applications”.

Created by Prof. Austin Tate and Dr. Gerhard Wickler, the course is offered at multiple levels of engagement from an “Awareness Level” to “Foundation Level” and a more involved “Performance Level” which included programming and other assignments. It has successfully run on the Coursera platform in 2013, 2014, and 2015.

Course materials include YouTube videos, weekly slides, quizzes, supplements, assignments, exams, and a Second Life virtual learning space and group.

The course materials are shared under the CC BY-NC-SA 3.0 licence.

 

Visit the AI Planning and MOOC Course Materials webpage

Learn more about the Artificial Intelligence Applications Institute at the University of Edinburgh

Go to the full AI Planning playlist on YouTube

 

 

Videos

 

Week 1

0.0. AIPLAN – Introduction 

1.0 AIPLAN – Welcome 

1.1 AIPLAN – What is Planning?

1.2 AIPLAN – Conceptual Model

1.3a AIPLAN – Planning and Search

1.3b AIPLAN – Planning and Search

1.4 AIPLAN – Example Problems

[Feature] AIPLAN – Artificial Intelligence Planning for Robots

1.5 AIPLAN – Context Practical Systems

1.6 AIPLAN – Context Tasking Execution Agents and Plans

1.7 AIPLAN – Context Example Planners

1.8 AIPLAN – Context Planning Plus Plus

 

Week 2

2.0 AIPLAN – Week 2 Introduction

2.1 AIPLAN – Heuristic Strategies

2.2 AIPLAN – A* Tree Search

2.3 AIPLAN – Properties of A*

2.4a AIPLAN – A* Graph Search

2.4b AIPLAN – A* Graph Search

2.5 AIPLAN Good Heuristics

[Feature] AIPLAN – Nils Nilsson on A* and STRIPS

2.6a AIPLAN – Structures States

2.6b AIPLAN – Structured States

2.7a AIPLAN – Structured Operators

2.7b AIPLAN – Structures Operators

2.8a AIPLAN – Domains and Problems

2.8b AIPLAN – Domains and Problems

2.8c AIPLAN – Domains and Problems

2.9a AIPLAN – Forward Search

2.9b AIPLAN – Forward Search

2.10 AIPLAN – Backward Search

 

Week 3

3.0 AIPLAN – Week 3 Introduction

3.1 AIPLAN – Partial Plans

3.2a AIPLAN – Plan Refinements

3.2b AIPLAN – Plan Refinements

3.3 AIPLAN – Plan Space Search

3.4 AIPLAN – Threats and Flaws

3.5 AIPLAN – PSP Algorithm

3.6a AIPLAN – PSP Implementation

3.6b AIPLAN – PSP Implementation

3.7 AIPLAN – The PoP Planner

3.8a AIPLAN – Task Networks

3.8b AIPLAN – Task Networks

3.9a AIPLAN – Methods

3.9b AIPLAN – Methods

3.10 AIPLAN – Decomposition

3.11 AIPLAN – Domains etc.

3.12a AIPLAN – STN Planning

3.12b AIPLAN – STN Planning

3.13 AIPLAN – HTN Planning

[Feature] AIPLAN – David Wilkins SIPE 2

 

Week 4

4.0 AIPLAN – Week 4 Introduction

4.1 AIPLAN – DWR Example

4.2a AIPLAN – Basic Planning Graph

4.2b AIPLAN – Basic Planning Graph

4.3 AIPLAN – Layered Plans

4.4a AIPLAN – Mutex Relations

4.4b AIPLAN – Mutex Relations

4.5 AIPLAN – Forward Graph Expansion

4.6a AIPLAN – Backward Graph Search

4.6b AIPLAN – Backward Graph search

4.7 AIPLAN – Graphplan Algorithm

[Feature] AIPLAN – Joreg Hoffmann on Heuristic Search

4.8 AIPLAN – Planning Graph Heuristics

4.9 AIPLAN – Pattern Databases

4.10 AIPLAN – The FF Planner

 

Week 5

5.0 AIPLAN – Week 5 Introduction

5.1 AIPLAN – AI Planning Execution DS1

5.2 AIPLAN – AI Practical Planners

[Feature] AIPLAN – Brad Clement AI Planning for Space

5.3 AIPLAN – Before Planning 

5.4a AIPLAN – Plan Generation

5.4b AIPLAN – Plan Generation

5.5 AIPLAN – Scheduling

5.6 AIPLAN – After Planning

5.7 AIPLAN – Conclusion 

 

Additional Videos

A.1. AIPLAN – Nonlin Demos

A.1. AIPLAN – Nonlin Demos 720×480

A.2. AIPLAN – O Plan Unix Systems Admin

A.3. AIPLAN – I-X CoSAR-TS

A.4. AIPLAN – I-X I-Globe Sensemaker

[Feature] AIPLAN – Arturo Gonzalez Ferrer AI Planning in Medicine

[Feature] AIPLAN – AI Planning for Space Supplement

 

 

Image: Abstract-hi-tech-cyber-technology by Activeda on Pixabay, CC0 Public Domain