10 votes

Selecting the right technique to predict disease from symptoms

I think you're coming at your problem slightly wrong... what you're essentially talking about is a belief network. You may want to look into existing Bayesian Learning techniques to get your head ...
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10 votes

What are examples of approaches to create an AI for a fighting robot in an MMO game?

I would set up a list of goals for your bot. These could be 'maintain a minimum level of health', 'knock out human player', 'block way to location X', etc. This obviously depends on the domain of your ...
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  • 5,062
8 votes

What are examples of approaches to create an AI for a fighting robot in an MMO game?

Oliver Mason's answer is great for specific methods and tools to use, but I wanted to pull out a more general principle which was mentioned in a comment. The distinction your friend is making is not ...
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  • 181
7 votes

Is it possible to clean up an audio recording of a lecture using some type of AI system?

Yes, it is possible. Usually, the noise reduction is done using regular signal processing methods, such as spectral subtraction due to demand for low latency. But, of course, modern methods of deep ...
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  • 171
6 votes
Accepted

Apart from Reinforcement Learning, are there any other machine learning approaches to play video games?

As I see it, it all comes down to game theory, which can be said to form the foundation of successful decision making, and is particularly useful in a context, such as computing, where all parameters ...
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  • 6,067
6 votes
Accepted

What are the best known gradient-free training methods for deep learning?

There are several different algorithms that can be used for gradient free neural network training. Some of these algorithms include particle swarm optimization, genetic algorithms, simulated annealing,...
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5 votes

Which algorithms can we use on games with high branching factors (e.g. Connect6)?

Typically, Monte-Carlo Tree Search (MCTS) actually is the go-to "solution" for such problems with large branching factors. I can understand that "vanilla" MCTS may still have unsatisfactory ...
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  • 9,379
5 votes

Are there any algorithms that can measure the concept similarity between texts?

Doc2Vec Doc2Vec comes to mind, here's the original publication. The approach has been shown to be very successful for certain NLP-based problems, though I haven't personally used it for a project yet....
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5 votes
Accepted

What is the typical AI approach for solving blackjack?

Blackjack is usually modelled using Monte Carlo (MC) Methods. There is a lot of literature on MC methods which is interesting on its own right but here is a paper describing how MC is applied to ...
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5 votes

How can I use neural networks for detecting TV channel logos in video frames?

To perform image recognition you have to find a way to represent an image with certain features. One of the defining characteristics of a good image recognition algorithm are it's ability to detect ...
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  • 1,146
5 votes
Accepted

How is the AI in 3d games implemented?

Overlap between AI and "Game AI" Nowadays, if you search for AI online, you will find a lot of material about machine learning, natural language processing, intelligent agents and neural ...
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  • 23.9k
4 votes
Accepted

How do I know if my backpropagation is implemented correctly?

Don't feel too bad for having gotten it slightly wrong because backpropagation is notoriously difficult to implement [1]. There is a technique called gradient checking, which you can implement to test ...
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4 votes
Accepted

Are there RL algorithms that also try to predict the next state?

Yes, there are algorithms that try to predict the next state. Usually this will be a model based algorithm -- this is where the agent tries to make use of a model of the environment to help it learn. ...
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4 votes
Accepted

Is there a standardized method to train a reinforcement learning NN by demonstration?

Yes, this is known as imitation learning, which can be divided into inverse RL (i.e. learn a reward function from demonstrations, then apply RL), and behaviour cloning (supervised learning applied to ...
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  • 33.8k
3 votes
Accepted

Would machine learning be suitable for finding the seed of a random number generator?

Machine Learning is a bad fit to this problem. Even simple PRNGs that are not suitable for use in simulators (such as rand()) are varied enough that it is very ...
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  • 23.9k
3 votes
Accepted

What are the approaches to predict sequence of $\pi$ numbers?

Pseudo-random number generators are specifically defined to defeat any form of prediction via 'black box' observation. Certainly, some (e.g. linear congruential) have weaknesses, but you are unlikely ...
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3 votes
Accepted

Which machine learning approach should I use to estimate how many products a research group should have to improve its category?

I believe you want a neural network that can predict future values of multiple variables given multiple inputs. This belongs to the general time series forecasting problem. One of the best neural ...
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  • 241
3 votes

Are there local search algorithms that make use of memory to give better solutions?

Tabu search uses memory to rule out parts of the neighborhood for local search, allowing the trajectory to typically pass through local optima instead of getting stuck in them.
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3 votes

Are there local search algorithms that make use of memory to give better solutions?

You could parallelize the search by dividing the global space in distinct regions/subsets. Then apply in each region a local search. This way you can search the global space systematically, more ...
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  • 227
3 votes

What are examples of approaches to create an AI for a fighting robot in an MMO game?

You can train your bot using reinforcement learning (in particular Q-Learning). The most important part of the RL is a reward function. If we want agent to do some thing specific, we must provide ...
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3 votes
Accepted

How to determine the quality of synthetic data?

Due to subjective nature, quantitative evaluation of synthetic images is difficult in general. However, there are metrics like Inception Score or FID score that are used for evaluation of generative ...
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  • 238
3 votes
Accepted

How do I use machine learning to create an optimization algorithm?

Machine learning has been used to automatically learn new optimization/learning algorithms. This task is often known as meta-learning, i.e. you learn to learn, in this case, an optimization algorithm, ...
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  • 33.8k
2 votes
Accepted

Which algorithm can I use to convert abbreviated words to the original ones?

Take a look at using a skip gram model to find what the abbreviated text is. The skip gram model turns a word into a vector, which allows it to be processed by other machine learning algorithms. Or, ...
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2 votes

How can I identify the car (stored in a database) that corresponds to the car in the new image?

Model of the car What you want to do is close to one-shot image recognition. You have not 1, but 3-4 examples of each car, but that is still a small amount, especially considering the car looks ...
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  • 203
2 votes
Accepted

How to add contextual follow up like Google Assistant

You would need to keep track of the current topic, and references. So, for example, a query When is the next train from London to Birmingham? would result in topic = TRAIN_TRAVEL start-loc = London ...
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  • 5,062
2 votes

What are some good approaches that I can use to count the number of people in a crowd?

Here a convolutional neural network (cNN) based approach is presented: Image Crowd Counting Using Convolutional Neural Network and Markov Random Field This blog post has more of a tutorial character ...
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  • 225
2 votes
Accepted

Which algorithm can I use to minimise the number of wins of 2 weapons that fight each other in a game?

I'm going to start by trying to restate your problem as I understand it. You have a game which contains weapons. Weapons are characterized by 5 different numbers, which can range over different ...
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2 votes
Accepted

Given a set of images that are not divided into groups, which algorithm should I use to do that?

This is called "clustering" , If the network is already trained with data that has similar features as of the "symbols", you can use that network with its last classification layer removed , then run ...
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