AI News, Talk:Artificial Intelligence
- On Sunday, September 30, 2018
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This book is intended as a central AI book, into which all other AI content will be merged (with exception of wikiversity articles and study guides).
AI is a rather large field (especially considering its age) so dividing it into small easily digestible chapters takes some effort.
If this book is ever going to be used in the classroom (or other learning environments) people will need to be able to pick and choose according to their interests or curriculum.
Chapters should therefore be as much standalone as possible, and required knowledge should be described clearly (both in terms of previous chapters and other knowledge (such as a basic grasp of programming structures or familiarity with Linear Mathematics).
think the basics of AI can be divided into around seven areas (like logic, machine learning, language etc.) To allow us to go into the more complicated areas as well (such as reinforcement learning or advanced neural models), I propose to set up a 'tiered' system.
The first section would describe basic techniques and knowledge (such as logic and state space search ), that can be read in any order and serve as required knowledge for the rest of the book.
Section two would describe the various subfields of Artificial Intelligence, based on the content of the first section (how predicate logic is used natural language processing and knowledge engineering, how state space searches are used in gameplay and nlp etc.) The reader is assumed to be familiar with the stuff from the first section.
Section four would serve to describe the very latest techniques, that borrow from different fields of AI, or very specific subjects that have developed their own body of knowledge and techniques (such as Machine Vision).
Coverage is going to be driven by what I currently work on, but if you need a specific knowledge engineering examples at any point, let me know and maybe we can help each other out.
What he did was create a problem at the beginning of the book, and then chapter by chapter after about chapter 10, he would start building a program to solve this problem.
I've played 'robocode' before, and neural networks, pattern matching, and so forth were all beaten by a simple statistical analysis of the enemy.
I think that the first chapter should be a background chapter, talking about: logic, search, optimisation, probability theory and inference.
Sectioning as described in the schools of thought section, in the wikipedia pages, is becoming all the more difficult with so many hybrid systems developed.
Another problem is the definition of terminology such as machine learning (any adaptive system can technically be considered as part of ML), and reinforcement learning (any AI technique can be applied to achieve this).
Risk, maybe you should move it to the module page – maybe some index structure could self-emerge from this :-) If I went into to much detail, forgive me and remove it.
Headings like 'Section 2: Basic AI topics' and 'Section 3: More advanced topics and techniques' add to the confusion, albeit I appreciate the efforts that has been done.Connection 13:54, 7 March 2006 (UTC)
human intelligence, you can't give a step by step instruction since there are many completely different ways that head in different directions that didn't produce any better results than the other, e.g.
added the Discrete mathematics prerequisite because I'd expect it to cover the 'review' aspects of the first section as it's currently listed (propositional logic, searching, probability).
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