AI thoughts

Witchcraven · 2008-07-24T17:07:42

So I was pondering casually what exactly makes intelligence so useful, as I am sure many of us had, especially those who work in AI. One idea I had was that abstraction and intuition probably may be two possible, and obvious sources. By abstraction, I mean the mechanism that makes polymorphism so useful. It gives you something simple to work with, that removes the need to think about other intermediate steps. For example, in polymorhpism you would need to think about conversion between types more than you would without it. It is somehow just nicer to work with. That one ability alone seems to give a huge mental advantage. I say intuition is important because if you get a few levels of abstraction and you need to solve a problem with concepts in a different layer of abstraction, navigating that by direct analysis can be very time consuming or difficult to do. For example in physics a force is a fairly basic thing to work with. Many concepts build on the idea of the force, and allow for ways to work with forces indirectly. One notable example is energy conservation. As a physics student, I thank god every day that energy seems to conserve. Some problems would be just terrible or maybe even impossible to solve analytically with just the idea of the force. But sometimes you do need to work backwards in abstraction levels (from energy to force). That can sort of thing can often be very hard to do. With intuition you can sort of guide yourself in situations like that to solutions, although you cant really explain why you go in some direction. Are these ideas totally obvious? Not true? What has been done in AI that explores these aspects of mental abilities? Are there abstraction algorithms out there that abstracts concepts in software? Maybe start with a simple interpreted programming language that can take simple commands in any order, during run time. This would be layer 0 of abstraction. Then a second layer of a finite number containers are created that represent the next level of abstraction. This new layer would randomly be populated with a small number of commands to the language. Any number of subsequent abstraction layers could be created and populated with references to containers in a previous layer. Then you could execute some number of containers in an abstraction layer, and they would each chain down and create some sort of complex pattern in the interpreter. The intuition would be what executes containers in an abstraction layer. It would probably a genetic algorithm or neural net of some sort. It would find what execution patterns of an abstraction layer are useful. Has this sort of thing been done before? Does it work? I do not really spend much in time in AI, so I am not sure what is out there.

Artificial Intelligence Programming

Started by Witchcraven July 23, 2008 03:04 AM

10 comments, last by losethos 16 years, 6 months ago

IADaveMark

3,839

July 24, 2008 10:21 AM

Quote:
Original post by Daerax
Speaking of Behaviour, I am a beginner and I cannot find anything on Behavio?ur Trees beyond a AI Gamdev post and a metapost on IA on AI. What is it really in more traditional terms?

I've been poking Alex about changing some of the layout of the site. Here's part 1 of a 3 video presentation on BTs that he did for GDC Lyon last year. It's more than an hour to watch all 3... go grab some popcorn first.

And thanks for the congrats folks.

Dave Mark - President and Lead Designer of Intrinsic Algorithm LLC
Professional consultant on game AI, mathematical modeling, simulation modeling
Co-founder and 10 year advisor of the GDC AI Summit
Author of the book, Behavioral Mathematics for Game AI
Blogs I write:
IA News - What's happening at IA | IA on AI - AI news and notes | Post-Play'em - Observations on AI of games I play

"Reducing the world to mathematical equations!"