# Questions tagged [artificial-intelligence]

Questions about design and properties of agents that act in a dynamic environment and make decisions towards some goal without user control.

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### What does the posterior probability of a variable mean in the Bayes' rule?

I have been studying Artificial Intelligence and I have noticed that the Bayes' rule allows us to infer the posterior probability if a variable. But, my question is, what does the word, or phrase, '...
3k views

### iterative lengthening search example

I am looking for an example of the "iterative lengthening search". I have searched and I was only able to find definitions like iterative lengthening search an iterative analog to uniform cost ...
955 views

### How to recognize a STRIPS planning problem has no solution?

Strips –Stands for STanford Research Institute Problem Solver (1971). STRIPS Pseudo code - ...
41 views

### How would one construct conjunctively local predicate of order k for checking if a shape is Convex?

I was reading Minsky's and Papert's book on perceptrons and it had the definition of conjunctively local as follow (look at the last images if its still unclear): A predicate $\psi$ is conjunctively ...
201 views

I've been reading some papers on reinforcement learning. $$\Delta w=\frac{\partial ln\ p_w}{\partial w}r$$ I often see expressions, similar to the above one, where the weights (denoted by $w$) are ...
34 views

### Can high-order unification be applied to programming by example?

In 2007, it has been proven that high-order unification is decidable on the pattern matching case. If that is true, what is stopping someone to write an equation like: ...
395 views

### What kind of Neural Network (if any) could fit two sets of data points?

I have two datasets, one of animal migration patterns (collected over the course of a couple years) that consists of many points on an x, y plane (latitude, longitude), and the other of ocean surface ...
492 views

### Can the effective branching factor be negative?

I've implemented A* algorithm in Python, after that I calculated the effective branching factor $B^*$ $$T+1=1+B^*+(B^*)^2+\dots +(B^*)^L$$ where $T$ is the number of expanded nodes. My question ...
253 views

### Guessing the best choice to maximize returns

There are $N$ number of people and $X$ amount of objects with different values. Each person will choose an object and will obtain that objects value. If multiple people choose the same object then the ...
12k views

### Nim game tree + minimax

Problem : Two players have in front of them a single pile of objects, say a stack of 7 pennies. The first player divides the original stack into two stacks that must be unequal. Each player ...
7k views

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### Understanding Alpha Beta Pruning: Why do we ignore the values of a unsearched tree after the first leaf, can they not include acceptable values too?

So this is my question. I am trying to understand this part of the book: At d) why do we stop looking at the other nodes in that branch? There could be a acceptable value next to the 2? I am just ...
46 views

### The task of recognizing game units in the screenshot

I'm new to computer vision and I want to solve the task of recognizing the game units of the game Clash Royale in the screenshot. Briefly, there are about 70 different types of gaming units belonging ...
1k views

### What kind of pattern recognition algorithm would Facebook use to detect suicidal users?

Facebook announced that it would employ a machine learning "reporting process using pattern recognition in posts previously reported for suicide" (https://newsroom.fb.com/news/2017/03/building-a-safer-...
72 views

### What determines the number of inputs and outputs when initialising weights in a convolutional neural network?

Following Deep MNIST for Experts tutorial on Tensorflow, I realize I don't understand where the choice of numbers comes from when initializing weights. In the tutorial, they first show the below ...
30 views

### how to approximate a very complex optimal policy when the distance function is unknown

A policy $P$ is defined as a set of parameters. We want to know the optimal policy $O$, which certainly exists but unfortunately unknown. $D(P)$ shows how far $P$ is from $O$. The function $D$ itself ...
716 views

### Semantic natural language processing - from texts to logical expressions? Universal knowledge base?

My question is - is there a semantic natural language processing that tries to understand the meaning of the texts and that tries to derive the consequences of the understood meaning? Is there a ...
269 views

### Convergence of Markov model

I was learning Hidden Markov model, and encountered this theory about convergence of Markov model. For example, consider a weather model, where on a first-day probability of weather being sunny was 0....
402 views

### decidability of artificial intelligence

Not sure whether this is the correct place to post the question. some of my terms might not accurate. currently AI is used for classification, inference, and so forth, is AI problem decidable? for ...
844 views

### Understanding the Broyden–Fletcher–Goldfarb–Shanno Algorithm to Select Weights for Neural Nets

I am trying to train and implement a Neural Network. I was reading a few articles, learning about their principles and the math that goes behind them. However, while I was trying to understand the ...
134 views

### Reinforcement Learning - Q Learning

I am having trouble understanding the following problem and Q learning in general. What I know so far about Q learning is that Q-learning is a model free method, i.e., it doesn’t need to learn P(s’|...
70 views

### How should i guide a program to perform correct things? [closed]

I want to make a small model of A.I. which can learn itself. I am inspired by 1000+ monkey theorem which states that if 1000+ monkey bangs a keyboard for enough long, then they will eventually produce ...
194 views

### How do I stop “cheating” in reinforcement learning (MLP+Evo. Algorithm)?

I have a two hidden-layer MLP. I am trying to teach it classification of the sine function. For instance, if there is an [x,y] point above the sine function, the ANN should classify that point as a 1. ...
132 views

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### What is the purpose of Bayesian networks?

I have seen a lot of explanations of what Bayesian networks are, but I simply cannot wrap my head around their use in code. So here is my three part question. Am I right in my definition of Bayes ...
17 views

### How are image processing and computer vision related to artificial intelligence.?

We have often heard both terms image processing and computer vision in AI sessions But i am confused, how they both are related to artificial intelligence?
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### Why aren’t (type theory based) automated theorem provers efficient?

Note: my main experience with theorem provers is with Type theory based proof-assistant, rather than an actual automated theorem prover. It is obvious why naive automated theorem proving is ...