# Tag Info

Accepted

### What are the differences between A* and greedy best-first search?

Both algorithms fall into the category of "best-first search" algorithms, which are algorithms that can use both the knowledge acquired so far while exploring the search space, denoted by $g(n)$, and ...
• 40.2k
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### Why does the discount rate in the REINFORCE algorithm appear twice?

The discount factor does appear twice, and this is correct. This is because the function you are trying to maximise in REINFORCE for an episodic problem (by taking the gradient) is the expected return ...
• 31.7k
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### What are the main algorithms used in computer vision?

There are many computer vision (CV) algorithms and models that are used for different purposes. So, of course, I cannot list all of them, but I can enumerate some of them based on my experience and ...
• 40.2k
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### What artificial intelligence strategies are useful for summarization?

The following post has a bit of math, which I hope helps to explain the problem better. Unfortunately it seems, this SE site does not support LaTex: Document summarization is very much an open ...
• 1,315

### Why does the discount rate in the REINFORCE algorithm appear twice?

Neil's answer already provides some intuition as to why the pseudocode (with the extra $\gamma^t$ term) is correct. I'd just like to additionally clarify that you do not seem to be misunderstanding ...
• 10.2k
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### How does the Jetson AI write its screenplays?

It appears to use Recurrent NNs (RNNs) that have a 'Long Short-Term Memory' (LTSM) architecture. Here's a summary of the development process that the author, Ross Goodwin, went through to create it. ...
• 7,256

### Cropping image using ML?

Yes, this is possible. There is actually a pretty easy way that doesn't even require machine learning and can be implemented with a small amount of code. You just use a framework for image processing ...
• 1,684
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### What are the limitations of the hill climbing algorithm and how to overcome them?

As @nbro has already said that Hill Climbing is a family of local search algorithms. So, when you said Hill Climbing in the question I have assumed you are talking about the standard hill climbing. ...
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### What are the limitations of the hill climbing algorithm and how to overcome them?

Hill climbing is not an algorithm, but a family of "local search" algorithms. Specific algorithms which fall into the category of "hill climbing" algorithms are 2-opt, 3-opt, 2.5-opt, 4-opt, or, in ...
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### Which machine learning algorithm is used in self-driving cars?

It will not be single DNN architecture, rather it will be a collection of different DNN architectures that are used together to make the final decision. Convolutions are using the images/videos from ...
• 531
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### What is the difference between local search and global search algorithms?

The difference between a local search algorithm (like beam search) and a complete search algorithm (like A*) is, for the most part, small. Local search algorithms will not always find the correct or ...
• 1,235

### How to determine if an Amazon review is likely to be fake using text classification

This will not be that hard of a problem once you have a lot of training data. But, before you have a lot of training data, you will need to get some training data one way or another. You will need a ...
Accepted

### MCTS: How to choose the final action from the root

By far the most commonly used strategy is to select the child with the highest number of visits. This is as described in the 2008 paper you linked. It's also what's referred to as the "robust child" ...
• 10.2k

### In RL, if I assign the rewards for better positional play, the algorithm is learning nothing?

What you are proposing is closer to a heuristic for searching than a reward for RL. This is a blurred line, but generally if you start analysing the problem yourself, breaking it down into components ...
• 31.7k

### Term for algorithms that are not trained

The word "Artificial intelligence" refers to machines being able to have intelligence that of humans/animals. The meaning of the word was even discussed on this site. So it's up to your ...
• 206
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### Selecting the right algorithm to predict disease from questions

There is no defined rules for choosing a machine learning algorithm to learn some type of pattern. However, there are some guidelines to help you better select an algorithm which will yield a higher ...
• 470

### What algorithm should I use to classify documents?

Text approach: Use LDA (Latent Dirichlet Allocation). LDA is unsupervised. Feed it in corpuses of text from the various documents (i.e. OCR them and feed LDA the results of OCR). It will then cluster ...
• 86
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### Do you need single or multiple networks to detect multiple faces?

AFAIK, normally detection algorithms work in a sub-window of the image and not the whole of it. For example, for a specific size and orientation you slide a sub-window on the image and extract sub-...
• 391

### Which machine learning algorithm is used in self-driving cars?

What you are calling 'analyzing the surroundings' is generally referred to as perception. Self-driving cars sense their surroundings using cameras, radars, lidars often combining or fusing more than ...
• 181

### Which machine learning algorithm is used in self-driving cars?

Self-driving cars use a combination of both supervised as well as reinforcement learning. Huge amounts of sensor data are recorded in real-time. This data can be used to train all sorts of supervised ...

### Why is the larger value, as opposed to the smaller one, chosen, in the hill climbing algorithm?

When we climb a hill: We move higher in altitude. The person who is climbing, will always look for rocks/mud on the hill that are higher, so that he can climb higher. That is what the algorithm does ...
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### Why does the discount rate in the REINFORCE algorithm appear twice?

It's a subtle issue. If you look at the A3C algorithm in the original paper (p.4 and appendix S3 for pseudo-code), their actor-critic algorithm (same algorithm both episodic and continuing problems) ...
• 131

### Can machine learning be used to improve the average case complexity of an algorithm?

To the best of my knowledge, there haven't yet been many academic publications in this area, which could be broadly said to fall within Search-Based Software Engineering. Here are the ones I know of. ...
• 7,256
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### How do I choose the search algorithm for a particular task?

The choice of the most appropriate search algorithm for a particular task is often based (but not exclusively) on its time complexity, space complexity, termination (if the algorithm always halts), ...
• 40.2k
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### How to find optimal mutation probability and crossover probability?

As @Oliver Mason says, picking the parameters that control the behavior of a GA (which are sometimes called "hyperparameters") is historically more of an art than a science. The evolutionary ...
• 9,237
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### Is there any computer vision technology that can detect any type of object?

TL;DR This is possible. You need a correctly labeled dataset. Your dataset has two labels: $y\in \{\text{background},\text{object in frame}\}$ or simply $y\in \{0,1\}$ This labelling avoids ...
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### What are the main algorithms used in computer vision?

Computer vision is a wide field, and besides the fact that deep learning dominates, there are still many, many other algorithms that see widespread use in both academia and industry. For tasks such as ...
• 86

### Which machine learning algorithm is used in self-driving cars?

The most common machine learning algorithms found in self driving cars involve object tracking based technologies used in order to pinpoint and distinguish between different objects in order to better ...
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### What kind of algorithm is the Levenberg–Marquardt algorithm?

In the context of Neural Networks, Backpropagation (with Gradient Descent, to use its full name) and Levengerg Marquardt are both members of the broader family of gradient descent algorithms. ...
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### How to efficiently interpret phrases in a Python AI?

To compare the strings you can use Fuzzy string matching. FuzzyWuzzy is a python package that does this using the Levenshtein distance, which calculates the difference between two strings by counting ...
• 375

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