Fuzzy logic is logic where state membership is, essentially, a float with range 0..1 instead of an int 0 or 1. The mileage you get out of it is that things like, for example, the changes you make in a control system are somewhat naturally more fine-tuned than what you’d get with naive binary logic. … Read more
Backward chaining (a la Prolog) is more like finding what initial conditions form a path to your goal. At a very basic level it is a backward search from your goal to find conditions that will fulfil it. Backward chaining is used for interrogative applications (finding items that fulfil certain criteria) – one commercial example … Read more
Short answer: No. Long answer: Games actually aren’t all that complicated. It depends on what you’re talking about when you say “games” but the two contenders for most complex games would be 3D games and online games (particularly massively online games). The complication in 3D games comes from taking a model of a world and … Read more
I have been there, and I faced this problem. The ANN was made for fixed feature vector length, and so are many other classifiers such as KNN, SVM, Bayesian, etc. i.e. the input layer should be well defined and not varied, this is a design problem. However, some researchers opt for adding zeros to fill … Read more
I made a Markov chain chatbot for IRC in Python a few years back and can shed some light how I did it. The text generated does not necessarily make any sense, but it can be really fun to read. Lets break it down in steps. Assuming you have a fixed input, a text file, … Read more
I used to have a lot of fun coding my own robot with Robocode in college. It is Java based, the API is detailled and it’s pretty easy to get a challenging robot up and running. Here is an example : public class MyFirstRobot extends Robot { public void run() { while (true) { ahead(100); … Read more
When I was learning this part, I found it very confusing too, so I put together the two pseudo-codes from R.Sutton and A.G.Barto hoping to make the difference clearer. Blue boxes highlight the part where the two algorithms actually differ. Numbers highlight the more detailed difference to be explained later. TL;NR: | | SARSA | … Read more
From wikipedia: A genetic algorithm (GA) is a search technique used in computing to find exact or approximate solutions to optimization and search problems. and: Neural networks are non-linear statistical data modeling tools. They can be used to model complex relationships between inputs and outputs or to find patterns in data. If you have a … Read more
The training and validation sets are used during training. for each epoch for each training data instance propagate error through the network adjust the weights calculate the accuracy over training data for each validation data instance calculate the accuracy over the validation data if the threshold validation accuracy is met exit training else continue training … Read more