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Online Course

Artificial Intelligence Planning

University of Edinburgh via Coursera

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Overview

The January to March 2015 session was the final version of the course, but it remains open until March 2016 so that those interested can register and access all the materials. All assignments are available to try but will not score or be eligible for a statement of accomplishment. Soon after that date Coursera will no longer support the platform on which this course is built, but the course materials and videos will continue to be available via:

    http://www.aiai.ed.ac.uk/project/plan/ooc/ (AI Planning Course Home Page)
    http://bit.ly/aiplanmooc (Videos on YouTube)

The course aims to provide a foundation in artificial intelligence techniques for planning, with an overview of the wide spectrum of different problems and approaches, including their underlying theory and their applications. It will allow you to:

  • Understand different planning problems
  • Have the basic know how to design and implement AI planning systems
  • Know how to use AI planning technology for projects in different application domains
  • Have the ability to make use of AI planning literature

Planning is a fundamental part of intelligent systems. In this course, for example, you will learn the basic algorithms that are used in robots to deliberate over a course of actions to take. Simpler, reactive robots don't need this, but if a robot is to act intelligently, this type of reasoning about actions is vital.

Syllabus

Week 1: Introduction and Planning in Context
Week 2: State-Space Search: Heuristic Search and STRIPS
Week 3: Plan-Space Search and HTN Planning
One week catch up break
Week 4: Graphplan and Advanced Heuristics
Week 5: Plan Execution and Applications
Exam week

Taught by

Gerhard Wickler and Austin Tate

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Reviews for Coursera's Artificial Intelligence Planning Based on 7 reviews

  • 5 stars 43%
  • 4 stars 29%
  • 3 star 0%
  • 2 stars 29%
  • 1 star 0%

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  • 1
Kristina Š
by Kristina completed this course and found the course difficulty to be hard.
This was a nice course, and I'm a bit sad this was its last iteration. It could be improved by adding more real-life examples of techniques mentioned, this kind of felt a bit too theoretical. There were three tracks, and this is great, so anybody could have find the level of engagement he wanted for the class. I'm giving it +1 star because they really tried to engage the students in different ways.

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