Questions tagged [models]

For questions related to modelling external environment, functional models tuned through convergent methods such as artificial networks or fuzzy logic containers, loss models, semantic models, model-based reasoning, or other kinds of models used in AI research, development, or practice.

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17
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3answers
1k views

Are there any computational models of mirror neurons?

From Wikipedia: A mirror neuron is a neuron that fires both when an animal acts and when the animal observes the same action performed by another. Mirror neurons are related to imitation learning, ...
14
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3answers
4k views

What is the relevance of AIXI on current artificial intelligence research?

From Wikipedia: AIXI ['ai̯k͡siː] is a theoretical mathematical formalism for artificial general intelligence. It combines Solomonoff induction with sequential decision theory. AIXI was first ...
6
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3answers
113 views

To what does the number of hidden layers in a neural network correspond?

In a neural network, the number of neurons in the hidden layer corresponds to the complexity of the model generated to map the inputs to output(s). More neurons creates a more complex function (and ...
6
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1answer
128 views

How do I predict if it is rainy or not?

I'm building a weather station, where I'm sensing temperature, humidity, air pressure, brightness, $CO_2$, but I don't have a raindrop sensor. Is it possible to create an AI which can say if it's ...
6
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1answer
74 views

Correcting 'bad' translations in a sequence-to-sequence neural machine translation model

In working with basic sequence-to-sequence models for machine translation I have been able to achieve decent results. But inevitably some translations are not optimal or just flat-out incorrect. I am ...
5
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2answers
736 views

Are there any pretrained models for human recognition from all angles?

I need to be able to detect and track humans from all angles, especially above. There are, obviously, quite a few well-studied models for human detection and tracking, usually as part of general-...
5
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1answer
671 views

What is the difference between hypothesis space and representational capacity?

I am reading Goodfellow et al Deeplearning Book. I found it difficult to understand the difference between the definition of the hypothesis space and representation capacity of a model. In Chapter 5,...
5
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1answer
219 views

How can i program a “Intuitive Physics Engine" for a walking simulator?

In the paper Learning Physical Parameters from Dynamic Scenes, 2018 a framework is presented to program a probabilistic physics engine for simulating the movements of a puck. A noisy-Newtonian ...
5
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1answer
103 views

How to detect frauds in advertising business using machine learning?

I am very beginner to this world. I still learning the basics of Machine learning and AI but i have a problem at hand and i am not sure which technique or Algorithm can be applied on it. I am working ...
4
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2answers
1k views

What is the “thing” which is trained in AI model training

I am a newbie in the fantastic AI world, I have started my learning recently. After a while, my understanding is, we need to feed in tremendous data to train a or many models. Once the training is ...
4
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2answers
399 views

Rollout algorithm like Monte Carlo search suggest model based reinforcement learning?

From what I understand, Monte Carlo Tree Search Algorithm is a solution algorithm for model free reinforcement learning (RL). Model free RL means agent doesnt know the transition and reward model. ...
4
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1answer
152 views

Can a computer conclude following philosophical concepts from a story?

Say you have to enter a story to a computer. Now the computer has to identify the philosophical concept on which the story is based, say: Was it a "self-fulfilling prophecy"? Was it an example of "...
4
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1answer
310 views

State representation of position in 2D plane for Reinforcement Learning (Q Learning)

I recently finished Course on RL by David Silver (on YT) and thought about trying it out on simple application in Unity Game Engine, where I've built simple labyrint with ball and want to teach the ...
4
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1answer
2k views

What are the real world uses for SAT solvers?

Why somebody would use SAT solvers (Boolean satisfiability problem) to solve their real world problems? Are there any examples of the real uses of this model?
4
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3answers
147 views

What kinds of systems have so far failed to be modeled via supervised artificial network training?

Artificial networks model systems with a set of inputs and outputs and expected behavior. To train a network for modeling such systems, hundreds, thousands, or millions of example inputs-output pairs ...
4
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1answer
88 views

What approach should I take to model forecasting problem in machine learning?

I have a dataset which contains 4000k rows and 6 columns. The goal is to predict travel time demand of a taxi. I have read many articles regarding how to approach the problem. So, every writer tell ...
3
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2answers
84 views

How to distinguish AI modeling from implementation?

Quote from this Eric's meta post about modelling and implementation: They are not exactly the same, although strongly related. This was a very difficult lesson to learn among mathematicians and ...
3
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1answer
499 views

How does an unsupervised learning model learn?

How does an unsupervised learning model learn, if it does not involve any target values?
3
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2answers
100 views

Is a deep technical understanding of neural networks required outside of research?

To understand the inner workings of neural networks, a fair amount of mathematical concepts is required. Backpropagation alone is a challenging technique if you are not fluent in calculating local ...
3
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1answer
112 views

Neural network architecture for comparison

When someone wants to compare 2 inputs, the most widespread idea is to use a Siamese architecture. Siamese architecture is a very high level idea, and can be customized based on the problem we are ...
3
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1answer
172 views

Mathematical modelling of A.I algorithms

How does one even begin to mathematically model an A.I algorithm like alpha-beta pruning or even its thousands of variations, to determine which variation is best?
3
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2answers
893 views

Machine learning with graph as input and output

In my application, I have inputs and outputs that could be represented as graphs. I have a number of acceptable pairs of input and output graphs. I want to use these to train a model. I am looking ...
3
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1answer
91 views

Machine Learning - Is selected models combination good?

I've selected more than 10 discriminative (Classification) models, each wrapped with a BaggingClassifier object, optimized with a GridSearchCV, and all of them placed within a VotingClassifier object. ...
3
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0answers
36 views

How to know when a Environment will yield a deterministic model

Given enough experiment data on time taken for objects to fall to earth from different heights, one can create various models that will accurately predict the time it will take for an object falling ...
3
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3answers
124 views

How can a collaboration game be defined mathematically? [closed]

One of the common conceptions in AI is the idea of game theory. We see that in the predominance of chess and other games in the literature as metrics of AI success. We see it in the names of machine ...
2
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6answers
2k views

What is the difference between AI architecture and AI model?

What is the difference between AI architecture and AI models? Are both of them the same? If not, please distinguish both of them and give example of each.
2
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1answer
107 views

Next step after building the model in machine learning?

I understand the way we build a model but all of the online courses I've found end with this--I can’t find any course explaining the process utilising the model to address the problem. How do I use ...
2
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2answers
92 views

Machine learning and machine generated content conflict problem

Machine learning and NN trainings as a part of ML is based on data that was gotten from real world and inserted into virtual space by humans. Meanwhile NN are also used for data generation. Each year ...
2
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1answer
44 views

What are pros and cons of Bi-LSTM as compared to LSTM?

What are the pros and cons of LSTM vs Bi-LSTM in language modelling? What was the need to introduce Bi-LSTM?
2
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1answer
19 views

What is the difference between model and data distributions?

Is there any difference between the model distribution and data distribution, or are they the same?
2
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1answer
48 views

What are the main differences between skip-gram and continuous bag of words?

The skip-gram and continuous bag of words (CBOW) are two different types of word2vec model. What are the main differences between them? What are the pros and cons of both methods?
2
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1answer
514 views

Are mathematical models sufficient to create general artificial intelligence?

Are mathematical models sufficient to create general artificial intelligence? I am not sure if it is possible to represent e.g. emotions or intuition using mathematical model. Do we need a new ...
2
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2answers
249 views

How can one intuitively understand generative v/s discriminative models, specifically with respect to when each is useful?

I'm trying to gain some intuition beyond definitions, in any possible dimension. I'd appreciate references to read.
2
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1answer
37 views

What is the current state-of-the-art in unsupervised cross-lingual representation learning?

What is the current state-of-the-art in unsupervised cross-lingual representation learning?
2
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1answer
29 views

Will a .h5 file trained with Xception model work with Resnet50?

I have been running my 2013 server box since 2 weeks ago for training an AI model. I set up 30 epochs to run but since than it only ran 1 epoch as my PC config is super slow. But it generates 1 .h5 ...
2
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1answer
14 views

Should I model a problem with quantised output as classification or regression?

Say I have some data I am trying to learn, and I'm aware that the output is quantised in some way, e.g. I can get only get discrete values (0.1, 0.2, 0.3...0.9) in a finite range. Would you treat ...
2
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1answer
21 views

Is it mostly the case to train with available models

I quite often find projects using pre-trained model and using them as a starting point for their new model that learns something novel from thier dataset or on-live learning process - e.g. using a ...
2
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1answer
45 views

What is the state of the art in models of how the human brain performs goal-directed decision making? Can these models' principles be applied to AI?

What is the state of the art in models of how the human brain performs goal-directed decision making? Can these models’ principles and insights be applied to the field of Artificial Intelligence, e.g. ...
2
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3answers
95 views

Why are tree-based models more widely used in Medical Diagnosis?

In Ch-14.4 @ Pattern Recognition and Machine Learning by Bishop it is mentioned that tree-based models are more widely used in Medical Diagnosis. Apart from giving better performance, is there a ...
2
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0answers
19 views

Using ML for Enemy Generation in Video Games

I am attempting to make a 2-D platformer game where the player traverses through an evil factory that is producing killer robots. The robots spawn at multiple specific locations in each level and ...
2
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0answers
55 views

Why isn't there a model playing FPS like CoD or Battlefield already existing?

Assuming we had an unlimited time to train a model and a very powerful machine to use our model in real-time (hello quantum computer), I'd like to know why no one could achieve to build an AI able to ...
2
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0answers
50 views

Correlating two models to predict the output of one that corresponds to an output of the other

I am currently working on a problem and now got stuck to implement one of it's steps. This is a simple attempt to explain what I am currently facing, which is something that I am aiming to implement ...
2
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0answers
13 views

What is a good model for regression problem with binary features and small data?

I am trying to predict the solution time for riddles in which matchsticks are combined into digits and operators. An example of a matchstick riddle is 4-2=8. The solution for this riddle would be ...
2
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0answers
42 views

Which deep neural networks are appropriate for the detection of bombs?

This is a follow-up question from my previous post here about explosion detection. I gathered a dataset of explosions. As I'm new to Deep Learning in Keras, I'm trying to see what architecture best ...
2
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0answers
51 views

Designing state representation for board game

I am trying to write self-play RL (NN + MCTS http://web.stanford.edu/~surag/posts/alphazero.html) to "solve" a board game. However, I got stuck in designing boardgame same (input layer for NN). 1) ...
2
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0answers
169 views

Is iLQG a good algorithm for model-based planning with simple environments?

In their work Continuous Deep Q-Learning with Model-based Acceleration, the author demonstrate great results of applying Imagination Rollouts for model-based acceleration of learning. They test their ...
2
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1answer
143 views

Network representation for Q-Learning in carrom

I am trying to build an agent to play carrom. The problem statement is roughly to estimate three parameters (normalized) : force angle of striker position of strike Since the state and action ...
1
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1answer
46 views

What is a model and how is it designed?

I read these things on the internet like My model determines the future scope..." or My model gives accurate readings about what the score would be..." What are these models? How are they ...
1
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2answers
122 views

How to store datasets of lexical connections?

I'm investigating the possibility of storing the semantic-lexical connections (such as the relationships to the other words such as phrases and other dependencies, its strength, part of speech, ...
1
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1answer
31 views

Is the “symbol grounding” problem about building a physics engine?

In the past, most reinforcement learning agents were developed to solve existing domains. At first, a game was given, for example the snake game, and after a bit of training, the neural network was ...