Behavioral Mathematics for Game AI (Applied Mathematics) [Kindle Edition]
Author: MARK | Language: English | ISBN: B00B7REBDW | Format: PDF, EPUB
Download Behavioral Mathematics for Game AI
Download electronic versions of selected books Download Behavioral Mathematics for Game AI for everyone book 4shared, mediafire, hotfile, and mirror link Human behavior is never an exact science, making the design and programming of artificial intelligence that seeks to replicate human behavior difficult. Usually, the answers cannot be found in sterile algorithms that are often the focus of artificial intelligence programming. However, by analyzing why people behave the way we do, we can break down the process into increasingly smaller components. We can model many of those individual components in the language of logic and mathematics and then reassemble them into larger, more involved decision-making processes.
Drawing from classical game theory, "Behavioral Mathematics for Game AI" covers both the psychological foundations of human decisions and the mathematical modeling techniques that AI designers and programmers can use to replicate them. With examples from both real life and game situations, you'll explore topics such as utility, the fallacy of rational behavior, and the inconsistencies and contradictions that human behavior often exhibits. You'll examine various ways of using statistics, formulas, and algorithms to create believable simulations and to model these dynamic, realistic, and interesting behaviors in video games. Finally, you'll be introduced to a number of tools you can use in conjunction with standard AI algorithms to make it easier to utilize the mathematical models. Books with free ebook downloads available Download Behavioral Mathematics for Game AI (Applied Mathematics) [Kindle Edition] IXL Math and English Online math and language arts practice Membership Explore the benefits of a family or school membership and join the millions of students using IXL worldwide Wonders of Math The Game of Life The Game of Life or simply Life is not a game in the conventional sense There are no players and no winning or losing Once the pieces Mental Math Strategies for Elementary eHow Feb 02 2011 Mental Math Strategies for Elementary Mental math is not only about doing computations in your head it is about being able to problem solve and
Download electronic versions of selected books Download Behavioral Mathematics for Game AI for everyone book 4shared, mediafire, hotfile, and mirror link Human behavior is never an exact science, making the design and programming of artificial intelligence that seeks to replicate human behavior difficult. Usually, the answers cannot be found in sterile algorithms that are often the focus of artificial intelligence programming. However, by analyzing why people behave the way we do, we can break down the process into increasingly smaller components. We can model many of those individual components in the language of logic and mathematics and then reassemble them into larger, more involved decision-making processes.
Drawing from classical game theory, "Behavioral Mathematics for Game AI" covers both the psychological foundations of human decisions and the mathematical modeling techniques that AI designers and programmers can use to replicate them. With examples from both real life and game situations, you'll explore topics such as utility, the fallacy of rational behavior, and the inconsistencies and contradictions that human behavior often exhibits. You'll examine various ways of using statistics, formulas, and algorithms to create believable simulations and to model these dynamic, realistic, and interesting behaviors in video games. Finally, you'll be introduced to a number of tools you can use in conjunction with standard AI algorithms to make it easier to utilize the mathematical models. Books with free ebook downloads available Download Behavioral Mathematics for Game AI (Applied Mathematics) [Kindle Edition] IXL Math and English Online math and language arts practice Membership Explore the benefits of a family or school membership and join the millions of students using IXL worldwide Wonders of Math The Game of Life The Game of Life or simply Life is not a game in the conventional sense There are no players and no winning or losing Once the pieces Mental Math Strategies for Elementary eHow Feb 02 2011 Mental Math Strategies for Elementary Mental math is not only about doing computations in your head it is about being able to problem solve and
- File Size: 4185 KB
- Print Length: 476 pages
- Page Numbers Source ISBN: 1584506849
- Publisher: Course Technology PTR; 1st edition (March 5, 2009)
- Sold by: Cengage Learning
- Language: English
- ASIN: B00B7REBDW
- Text-to-Speech: Enabled
- Word Wise: Not Enabled
- Lending: Not Enabled
- Amazon Best Sellers Rank: #543,269 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
A lot what I think of a book comes from my expectations. The style, the content and the useful information that it provides me all factor into my opinion.
For starters, I do programming for a living. After 10 years of .Net Web sites and databases, I'm looking to expand my skill set. Not games, necessarily, but AI for sure. I tried a couple math books on Game theory, but they were still a few levels away from practical interpretation. This book brought it down to a level I could use.
In a nutshell, it's about how to program dice for an RPG. The scope is a little broader than that, but this is the main idea. In nontechnical language, the author discusses what the goals of AI are, how rational decisions are made, and how to use probability to generate irrational decisions to model an unpredictable world.
Math wise algebra would be a good idea, and maybe some basic understanding of calculus and statistics, but he gives sufficient background so that your understanding would not be hindered. The book doesn't really teach programming per se, so it really doesn't matter what language you use (although the examples are done in C).Specific algorithms, such was swarming and flocking, are also absent. The material here would be used after you have those ideas down...for example, you have your agents flocking, so now how does the flock decide what to do, and when?
This brings me to the one real draw back to the book. I could tolerate his jokes and stories about his kids, but I suspect some UMLs would have done wonders to make the material clearer. Use cases were almost there in his examples, but it just missed the mark. Maybe this was an attempt to keep the thinking less technical and open it to a wider market, but it is something he should have touched on.
The author, at one point, uses a personal anecdote about having agreed with his publisher about how the book should be this many pages, and he was working to fill up that much space. The good news is that the author put words, code, pictures, and diagrams on each of the pages in this book.
If you're looking for good descriptions of challenging topics, this is not the book for you. The diagrams are often confusing (inverting the x-axis for questionable reasons), the code takes up far too much space for the value it is supposed to convey, and the prose is bloated.
The author early on makes the distinction between "proscriptive" and "descriptive" mathematical models - making the point that we're not necessarily trying to find optimal behavior, we're trying to record plausible behavior. This is a reasonable decision, but the amount of work necessary to model the author's favorite example of "4 out of 5 dentists recommending sugar free gum to their patients that chew gum" seems overwrought for what could be accomplished in one line of code.
The author invents a term "response curves", which seems like an awkward name for a selection from a weighted list. He claims that these are necessary, because algorithmic functions don't offer enough flexibility to achieve the results he's looking for. His response curves are piecewise constant functions over a finite domain, and if you want the flexibility of his response curves without the discontinuities, look up splines - well understood, and supported by many libraries already.
The book lurches from dwelling on some easy ideas (scaling the output of a function to be between 0 and 1 and weighted averages) to briefly touching on more complicated ones (marginal utility).
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