General Game Playing

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5/10 stars
based on  6 reviews
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Cost FREE
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FREE

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Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
5003 reviews

Course Description

Learn about General Game Playing (GGP) and develop GGP programs capable of competing against humans and other programs in GGP competitions .
General Game Playing course image
Reviews 5/10 stars
6 Reviews for General Game Playing

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Dan profile image
Dan profile image
8/10 starsCompleted
  • 9 reviews
  • 9 completed
7 years, 10 months ago
Not sure this has many applications, but it was a fun class, and probably the only coursera class where I continue to improve the code started in class over a month after it has ended. The videos didn't add that much over the written material, and the written material may need some smoothing, but overall it's good. A few of the exercises were ill-conceived as even following instruction could result in a low grade, but this was only the first course iteration and all the other exercises were useful. The staff also seemed receptive to criticism and willing to further improve it. You can complete the class with or without programming, but for it to be a good experience I think you need to write your code. They offered a gamer framework in Java that could be expanded and resulted in many people writing their own players. I'm a programmer, but didn't know much about Java (but know C# which has many similarities) before this class and foun... Not sure this has many applications, but it was a fun class, and probably the only coursera class where I continue to improve the code started in class over a month after it has ended. The videos didn't add that much over the written material, and the written material may need some smoothing, but overall it's good. A few of the exercises were ill-conceived as even following instruction could result in a low grade, but this was only the first course iteration and all the other exercises were useful. The staff also seemed receptive to criticism and willing to further improve it. You can complete the class with or without programming, but for it to be a good experience I think you need to write your code. They offered a gamer framework in Java that could be expanded and resulted in many people writing their own players. I'm a programmer, but didn't know much about Java (but know C# which has many similarities) before this class and found it easy enough to implement a player once the first step of orienting oneself within the framework and where to find the various tools. They pointed to Eclipse as the IDE and I was quite pleased with it, except for code profiling I could do everything from the IDE and it even offered to-the- point suggestions to fix errors due to my lack of familiarity with Java. The 'logic' part of the class was a bit hard due to nomenclature, but looking at the game definitions and the examples in the notes cleared it up. A couple of things that I thought were weird about GGP: 1) all good implementations seem to use a coding approach called 'propnets' (similar to a digital circuit implemented in software that represents the game rules) that is only hinted at in class and requires much work without guidance if you aim at an efficient implementation. 2) some of the games seem specifically tailored to be exploitable (e.g. factorizable games) by algorithms that I guess may be of interest to the authors of the discipline or of those games but I still don't know how much of those methods translate to 'traditional' games. At the end of class the staff organized a competition, it was good fun. Writing a player to participate in the competition should be easy enough, but writing one that is not hopelessly dumb in all games is actually a LOT of implementation work beyond what was covered in class. Overall, I wrote a (general) game player (although its level of play is still medium-poor) as a result of this class, which is something I always wanted to try but never found the time before. I might even continue to improve it for months or years. General game programming has many similarities (e.g game trees, alpha-beta search, transposition tables) but also some differences with programming for a specific games. One difference is the performance hit of having to interpret the rules, but an even bigger difference is that you can't pre-build an euristic to evaluate game tree nodes (it was interesting to see how Monte Carlo tree search can partially address this).
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Dmitriy Borisenkov profile image
Dmitriy Borisenkov profile image
6/10 starsTaking Now
  • 4 reviews
  • 3 completed
7 years, 8 months ago
I have MS in computer science, but AI wasn't my specialization. I've studied some basics of logic programming and AI, but haven't taken advanced couses on the topic. The begining of GGP course is very promising, but actual workload is very small for such a complicated topic as GGP and hence the course itself provides low rate of learning the material (I think it's quicker to study general game playing by reading books and working on gameplaying bots on your own). But there are only a few courses on coursera which has something beyond standard grading policy including quizzes and programming assignments. Gameplaying robots competition strongly distigush this course among others.
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Duncan Murray profile image
Duncan Murray profile image
6/10 starsCompleted
  • 25 reviews
  • 24 completed
7 years, 10 months ago
I had no experience with Game Theory, but some exposure to AI and software development in general. The lectures are a bit too short and basically focus on the slides. The bulk of the course is around you setting up the pre-built Stanford Game playing software and implemented various game playing techniques through it. I found the mechanics of using this software a useful exercise, but would have liked to implement something myself instead (or as well as)
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Jim Humelsine profile image
Jim Humelsine profile image
2/10 starsCompleted
  • 7 reviews
  • 7 completed
7 years, 11 months ago
I've taken about 10 Coursera courses. This is the first one I didn't complete. The advertisement sounded great. The introduction lecture was very promising. The first serious lectures, about games being state machines and representing those statement machines via rules was interesting too, but then it all fell apart for me after that. I watched the lectures, which amounted to about 30 minutes per week, but that was about it. The lectures were basically the instructor reading the slides, and we never saw his face either. The instructor should be a student in a few MOOCs to get a sense of how they should be presented. If he only had time for one, I'd recommend the Python class from Rice. It was a programming course, involving games, that got it right.
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Darya Prokurat profile image
Darya Prokurat profile image
2/10 starsDropped
  • 8 reviews
  • 6 completed
7 years, 12 months ago
Strange course with specific language for describing games and strategies. Explanations in the lecture was not enough for me. (BS in Computer Science)
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Equanimous Creativity profile image
Equanimous Creativity profile image
4/10 starsCompleted
  • 33 reviews
  • 32 completed
8 years ago
I took this course first time it was covered on coursera. This course was a little disappointing for me. I had expected this to be an advance AI course and when ask for a syllabus they refereed to the online notes, which showed both basic and advance material. But as the course progressed we only got on average 15 minute of lecture per week, and for the first 8 weeks only the basic material like Minimax trees, Alpha-Beta pruning Heuristic and Monte Carlo search was covered. Materiel which is expected to be covered in an introductory AI course, but in an advance course it should be in the review material in the first few weeks. Only in the last two weeks was a few of the advance topic covered and not in great detail. Along the way you was recommended to write your own game player which you could enter in a competition at the end. I think the subject is interesting but more focus should be on the advance stuff and much lesser on basic ... I took this course first time it was covered on coursera. This course was a little disappointing for me. I had expected this to be an advance AI course and when ask for a syllabus they refereed to the online notes, which showed both basic and advance material. But as the course progressed we only got on average 15 minute of lecture per week, and for the first 8 weeks only the basic material like Minimax trees, Alpha-Beta pruning Heuristic and Monte Carlo search was covered. Materiel which is expected to be covered in an introductory AI course, but in an advance course it should be in the review material in the first few weeks. Only in the last two weeks was a few of the advance topic covered and not in great detail. Along the way you was recommended to write your own game player which you could enter in a competition at the end. I think the subject is interesting but more focus should be on the advance stuff and much lesser on basic stuff which students with an interests in AI have probably seen before.
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