Artificial Intelligence Planning
Offered By: University of Edinburgh via Coursera
Course Description
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:
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
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
Tags
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