I thought it was available for free online, but now that I look, all I'm
finding is this: http://aima.cs.berkeley.edu/



On Sun, Jan 27, 2013 at 5:36 PM, Chris Nolan <[email protected]>wrote:

> Yeah, I'm planning on taking Coursera's NLP course that starts in two
> weeks. Overall I really like the set up there (and they have more courses
> to choice from than Udacity), but I wish they didn't have such strict
> schedules, it's going to be extremely difficult for me as well. That's
> something I really like better that Udacity is doing. It puts more focus on
> learning and less on deadlines. Allows learning based on mastery versus
> learning based on time in the traditional way, as the Khan academy likes to
> talk about.
>
> Do you have Russell/Norvig's AI:A Modern Approach? It's the classic
> overview book, covering a little bit of everything in AI/ML. It's a little
> pricey but definitely worth buying and surprisingly goes into a good bit of
> detail (sometimes too much) for a general book. It has a chapter on
> robotics and path planning so probably covers the basics of what you're
> looking for. Some more advanced ones are Principles of Robot Motion and
> Computational Principles of Mobile Robotics, both of which are helping me
> trying to get some of the concepts you're talking about. Still a work in
> progress though.
>
> good luck,
> -Chris
>
>   ------------------------------
> *From:* Jim Bromer <[email protected]>
> *To:* AGI <[email protected]>
> *Sent:* Sunday, January 27, 2013 3:35 PM
> *Subject:* Re: [agi] I may be destined to be a hopeless dropout from
> online introductory courses in AI
>
> I d
>
> On Sat, Jan 26, 2013 at 1:50 PM, Chris Nolan <[email protected]>wrote:
>
> Yeah, I've head similar problems with some of the machine learning classes
> as coursera. I've really like udacity's program though, not sure if you've
> checked it out? They've got two AI courses, one the classic Intro to AI
> that covers a little bit of everything:
>
>
>
> I am taking a course on Coursera and Udacity.  I like both courses so
> far.  I just did not know something about a state transition system and I
> did not know how to pick up on the way the professor was explaining the
> information.  I misunderstood that something the professor had said was
> applicable to a state transition system.  I am looking forward to both
> courses although it is going to be difficult for me to adhere to the
> Coursera schedule.
> Jim Bromer
>
>
> I found
>
> I found that I have to use the textbook with
> On Sat, Jan 26, 2013 at 1:50 PM, Chris Nolan <[email protected]>wrote:
>
> Yeah, I've head similar problems with some of the machine learning classes
> as coursera. I've really like udacity's program though, not sure if you've
> checked it out? They've got two AI courses, one the classic Intro to AI
> that covers a little bit of everything:
>
> https://www.udacity.com/course/cs271
>
> I used the first version to help me with a general AI course I took last
> year. They also have a more advanced AI for Robotics class that goes into
> robot planning using probabilistic methods:
>
> https://www.udacity.com/course/cs373
>
> I'm taking this one now. Overall I like their set up better than
> coursera's (although it's still really good). They don't have as much
> classes, but they incorporate videos and short programmng quizes in a way
> that makes it easier to understand and apply. Their program is also
> self-paced so you don't have to worry about Coursera's deadlines, just
> learning the material and getting the work done. For both though, I've
> found I have to have a textbook for review and to get the full background
> and proofs behind the concepts. It just doesn't work for me otherwise.
>
> -Chris
>
>
>   ------------------------------
> *From:* Jim Bromer <[email protected]>
> *To:* AGI <[email protected]>
> *Sent:* Friday, January 25, 2013 7:29 PM
> *Subject:* [agi] I may be destined to be a hopeless dropout from online
> introductory courses in AI
>
> I am taking two Introduction to AI online courses and I am making quite a
> few mistakes.  Some of the mistakes are just plain mistakes. But some are
> due to annoying cutsieness.  Here is an example:
>
> True or False
> State transition systems can represent actions that occur in parallel.
>
> Well of course they can, but since this is an introductory course the
> answer has to be False.
> Ok, got that one right.
>
> A state transition graph may have multiple outgoing/incoming directed
> edges that are labelled with the same action.
>
> Well I had a feeling that was a trick question given the answer to the
> first question, and the answer is...True. True?  My best guess is that the
> term label was not being applied to *some particular* labelled actions but
> to the choice of actions at a particular state, whereas each state is the
> resultant of the action so they are thought of as particulars (like
> values)?  Maybe there is some other reasoning behind this but if there is I
> can't figure it out.
>
> This was from an introductory course in AI planning. AI Planning!  I find
> this stuff intensely annoying.  We cannot use a state transition diagram to
> diagram parallel actions?  (That would be impossible for anyone to even
> consider. Your mind can't handle it.)  But it can be used to represent
> multiple outgoing/incoming directed edges labelled with the same action?
> Is the teacher kidding? Maybe you guys who have already been through this
> see some error that I don't see, but I just don't see why the teacher
> cannot just come out and explain the conventions that are applied to
> terminology (like "state transition diagram") and save the quizzes for the
> good stuff. Why challenge the students with the professor's mastery of
> ambiguity?
>
> I make a lot of really dense mistakes in these courses.  I don't want to
> waste my time trying to outwit the teacher's challenges about computational
> phlogiston.
>
> Jim Bromer
>
>
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