For questions about artificial intelligence.

learn more… | top users | synonyms

1
vote
1answer
28 views

Markov Decision Process - Optimal policy invariance to scaling in the Utility Function

The title says it all. If i use a discounted Utility Function, why is the optimal policy invariant with respect tot the scaling of the Utility Function by a positive Factor?
1
vote
1answer
148 views

Gradient descent/ nonlinear optimization intuition needed

all. I'm taking an introductory AI class, and we're using the gradient descent algorithm to find the optimized/ lowest cost of a set of thetas (variable coefficients) to best fit a regression line. In ...
1
vote
1answer
111 views

i,j,k values of the theta matrix in neural networks

SO I'm looking at these two neural networks and walking through how the ijk values of Theta correspond to the layer, the node number, and either there are redundant values or I'm missing how the ...
0
votes
1answer
26 views

Bayesian Nets. No active path from X to Y, versus No inactive paths from X to Y

I am learning d-seperation in Bayes nets for my A.I. class. What this involves is considering all paths from some node X to Y (representing random variables) and seeing whether such paths are active ...
0
votes
1answer
44 views

probabilistic behaviour

I am trying to understand what 'probabilistic behaviour' in a 'deterministic model' means. I am reading this paper http://www.ulb.ac.be/sciences/use/publications/JLD/16.pdf but i find myself unable ...
3
votes
0answers
56 views

Are there some functions that cannot be optimized using calculus?

I've been working on a project to maximize a functions output using a genetic algorithm. However, from the limited calculus I know I thought there were methods to find the maximum of a mathematical ...
3
votes
0answers
462 views

Convert a WFF to Clausal Form

I'm given the following question: Convert the following WFF into clausal form: \begin{equation*} \forall(X)(q(X)\to(\exists(Y)(\neg(p(X,Y)\vee r(X,Y))\to h(X,Y))\wedge f(X))) \end{equation*} ...
2
votes
0answers
288 views

Modern mathematical theory on Neural Networks, Cellular Automata, Neuroscience

Is it possible for someone to do research on Neural Networks/Cellular Automaton/Neuroscience as an applied mathematician, for its theoretical development, especially based on some modern mathematics, ...
1
vote
0answers
27 views

feature selection for continuous variables

I wonder how exactly "feature selection" should be performed in case of continuous feature values. When feature values are discrete it is very straitforward to apply feature selection, but what to do ...
1
vote
0answers
37 views

Solomonoff induction , Shannon Entropy, Kolmogorov Complexity.

If Expected Kolmogorov Complexity equals Shannon Entropy why can't Shannon Entropy be used as an approximation of Kolmogorov Complexity in Solomonoff Induction? Regarding Kolmogorov Complexity and ...
1
vote
0answers
135 views

Estimating conditional probability as a function of time

My question relates to estimating from a time series a time dependent conditional probability without having a prior parametric model of anything. Suppose I have two variables: r and I, and each can ...
0
votes
0answers
21 views

ID3 algorithm and binary trees

You have a sample set of 8. You need to make a table such that if you run ID3 on it you get a binary tree with 5 leaf nodes. I'm stuck. I did lots of trial and error.
0
votes
0answers
7 views

Applying a Resolution to a Predicate with Substiutions

My professor handed us an exam review with the answers already filled in. On this one particular problem I have no idea how he came to the answers he did. Question: Apply a resolution to the ...
0
votes
0answers
27 views

Conjunctive normal form (~p->r) AND (~p->~r) <-> r

I need help converting following formula to conjunctive normal form. (~p->r) AND (~p->~r) <-> r By using equivalences i arrive to following result (((~p AND ~r) OR (~p AND r)) OR p) AND (~p OR ...
0
votes
0answers
5 views

What is a basic description of how diffusion mapping works?

I have been trying to get a basic understanding of diffusion mapping, and I think I understand the concept, but I am having trouble understanding the math behind it (I have knowledge of advanced math ...
0
votes
0answers
40 views

Concept Learning algorithm in Artificial Intelligence

Im going through Machine Learning in Artificial intelligence(Artificial Intelligence by George F Luger-Page 398) . Im going through the candidate elimination algorithm. There is this specific to ...
0
votes
0answers
22 views

How to transform one graph to a spectrum?

Recently, I studied a paper called "What Does Your Chair Know About Your Stress Level? It can be download at the link below. ...
0
votes
0answers
13 views

neural networks truth table uses of bias and weight

in a Truth table there are two additional columns for bias and weight, what is the correct purpose of the columns. i am having to build a randomiser application and would like to understand their ...
0
votes
0answers
35 views

An example shows the difference between inference in Bayesian network and Junction Tree

Why inference in Junction tree is more efficient? There are directed graph BN and the corresponded undirected graph transformed by Junction tree algorithm. The literature describes that inference in ...
0
votes
0answers
22 views

What elementary statistics (eg correlation) can help me with an Artificial Intelligence program I'm writing?

I am writing a crude Artificial Intelligence langauge/conversation computer program in java for a first year community college creative final assignment. I know some basic Statistics / Finite ...
0
votes
0answers
14 views

what is convergence in k Map?

I have a very small question related to unsupervised learning because my teacher have not use this word in any lectures. I got this word while reading tutorials. Does this mean if values are same to ...