The first step, in taking this game to the next level, is … …to have a very clear view of prior art! (and pardon me to say, the question doesn’t suggest that you have such an extensive insight into the matter [and you’re not alone, count me in ;-)]) Even, and maybe in particular, if … Read more
The question has already been answered for Lisp, so I’ll just comment on Prolog. Prolog was designed for two things: natural language processing and logical reasoning. In the GOFAI paradigm of the early 1970s, when Prolog was invented, this meant: constructing symbolic grammars for natural language that would be used to construct logical representations of … Read more
I’ll try to keep this short and sweet. One approach that is often used to solve these problems in simulation is a Rapidly-Exploring Random Tree. To give at least a little credibility to my post, I’ll admit I studied these, and motion planning was my research lab’s area of expertise (probabilistic motion planning). The canonical … Read more
This is similar to issues with trying to find a global minimum, where it’s easy to get stuck in a local minimum. Consider trying to find the global minimum for the profile below: you place the ball in different places and follow it as it rolls down the hill to the minimum, but depending on … Read more
“AI engine” can mean an awful lot of different things. What kind of “AI” are you looking for? Here is a list of some machine learning software. Many of them are open source (the linked page shows the licenses).
In the case of 11 line segments, you have 330 ways of choosing four segments. You could determine the likelihood of each combination making a quadrilateral, and grade that way. It is possible to have a Hough transform detect forms other than lines, though it becomes harder to visualise as the accumulator space would require … Read more
There are two parts to this question. The first part is “what is the form of function learned by these methods?” For NN and SVM this is typically the same. For example, a single hidden layer neural network uses exactly the same form of model as an SVM. That is: Given an input vector x, … Read more
Once a NN has been trained, for eg. using backprogation as mentioned in the question (whereby the backprogation logic has “nudged” the weights in ways that minimize the error function) the weights associated with all individual inputs (“outside” inputs or intra-NN inputs) are fixed. The NN can then be used for classifying purposes. Whereby the … Read more
All the cool bearded gurus in what’s left of AI research use Lisp 🙂 There are two big camps: Common Lisp and Scheme. They have different syntax, etc. Lots of good stuff written for both. Java is a very popular all-purpose language but a lot of the interesting stuff in AI / Functional Programming, such … Read more