Artificial Intelligence Planning

Product type

Artificial Intelligence Planning

Coursera (CC)
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Description

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

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.

About the Course

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…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

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.

About the Course

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.

About the Instructor(s)

Dr. Gerhard Wickler: Obtained his Ph.D. in 1999 at Edinburgh in the area of AI Planning. He went on to hold research positions in Italy, Belgium, and Germany, working in several areas of AI. Since 2004 he has been senior researcher at the Artificial Intelligence Application Institute (AIAI) within the School of Informatics at the University of Edinburgh, where he teaches the AI Planning course. Dr. Wickler regularly publishes in AI-related conferences and journals, reporting on his research in AI Planning and Intelligent Agents applied to emergency response. He is an active reviewer for a number of conferences and journals. He has been a member of the programme committees for various workshops and conferences, including the Intelligent Systems track at ISCRAM. He is currently lead scientist on an EPSRC and industry funded Autonomous and Intelligent Systems project using AI plan modelling in dynamic environments. In May 2010, he was elected onto the board of directors of the ISCRAM Association and has received the ISCRAM Distinguished Service Award.

Prof. Austin Tate: Director of the Artificial Intelligence Applications Institute (AIAI) and holds the Personal Chair of Knowledge-Based Systems at the University of Edinburgh. He is a Fellow of the Royal Academy of Engineering, Fellow of the Royal Society of Edinburgh (Scotland's National Academy), Fellow of the Association for the Advancement of AI, Fellow of the British Computer Society, Senior Visiting Research Scientist at the Institute of Human Machine Cognition (IHMC) in Florida, and on the editorial board of a number of AI journals. His research background involves advanced knowledge and planning technologies, with a focus on their use in emergency response and collaborative systems especially using virtual worlds. He is the Coordinator for the Virtual University of Edinburgh (Vue) and Coordinator for Distance Education in the School of Informatics at the University of Edinburgh.

Course 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 Week 4: Graphplan and Advanced Heuristics Week 5: Plan Execution and Applications

Recommended Background

The course is at an introductory level, but you will need a basic understanding of logic.

Suggested Readings

The course follows a text book, but this is not required for the course: Automated Planning: Theory & Practice (The Morgan Kaufmann Series in Artificial Intelligence) by M. Ghallab, D. Nau, and P. Traverso (Elsevier, ISBN 1-55860-856-7) 2004.

Course Format

5 week course with 10 hours of lecture material presented as videos. Quizzes and assessments throughout the course will assist in learning. Some weeks will involve some recommended readings. Discussion on the course forum will be encouraged.

FAQ

  • Will I get a certificate after completing this class?

    Students who complete the class will be offered a Statement of Accomplishment signed by the instructors.

  • Do I earn University of Edinburgh credits upon completion of this class?

    The Statement of Accomplishment is not part of a formal qualification from the University. However, it may be useful to demonstrate prior learning and interest in your subject to a higher education institution or potential employer.

  • What resources will I need for this class?

    Nothing is required, but if you want to try out implementing some of the algorithms described in the lectures you'll need access to a programming environment. No specific programming language is required. Also, you may want to download existing planners and try those out. This may require you to compile them first.

  • Can I contact the course lecturers directly?

    You will appreciate that such direct contact would be difficult to manage. You are encouraged to use the course social network and discussion forum to raise questions and seek inputs. The tutors will participate in the forums, and will seek to answer frequently asked questions, in some cases by adding to the course FAQ area.

  • What Twitter hash tag should I use?

    Use the hash tag #aiplan for tweets about the course.

  • How come this is free?

    We are passionate about open on-line collaboration and education. Our taught AI planning course at Edinburgh has always published its course materials, readings and resources on-line for anyone to view. Our own on-campus students can access these materials at times when the course is not available if it is relevant to their interests and projects. We want to make the materials available in a more accessible form that can reach a broader audience who might be interested in AI planning technology. This achieves our primary objective of getting such technology into productive use. Another benefit for us is that more people get to know about courses in AI in the School of Informatics at the University of Edinburgh, or get interested in studying or collaborating with us.

  • When will the course run again?

    It is likely that this course will be run once each year, but we intend to leave the community wiki open for development and use across course instances.

Provided by:

University: University of Edinburgh

Instructor(s): Gerhard Wickler, Austin Tate

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