How to infer correctly?

Question

How do AI based agents infer a decision that are not necessary rational but logical correct based on previous experience.

In the field of AI how do experts system infer, what kind of maths and probabilities are involved here?

I plan on creating an intelligent, but don't no where to start. Pointers or links to any resources would be grateful. Preferably a resources that describes the mathematical concept for those whom are not mathematical minded.

Answer 1

One approach is to use Propositional Logic or First Order Logic. The latter is more flexible.

First you define the current knowledge and then you can perform inferences applying rules. Prolog is a very powerful programming language for this purpose. In prolog you define you current knowledge using facts and then you can create rules that denote relationships. Then you can perform queries based on your facts and rules you defined.

Answer 2

I don't understand your question. In AI parlance, rationality is taken to mean, "Acting in a way, given a situation and a history, that is expected to maximize some performance measure." One does not sacrifice rationality, because that would be acting in a way not expected to maximize performance.

Maybe you are thinking that rationality and predicate- or first order logic are the same thing; they're not.

In any case, your question is too broad to really answer. But, I believe you'll want to start with basic probability, then specifically Bayesian probability and statistics, and then (having the correct tools) you can look into probabilistic AI techniques: Markov chains, Markov decision processes, etc. You can also look at machine learning techniques.

Be aware: These are not simple mathematics. There is no way around that.

Note that this answer speaks to my personal biases; it is not an exhaustive list of techniques.