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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, ...
13
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3answers
2k 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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1answer
123 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
71 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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3answers
96 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 ...
5
votes
2answers
330 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
votes
1answer
456 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
187 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
79 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
845 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
146 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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3answers
145 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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3answers
108 views

How can a collaboration game be defined mathematically?

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 ...
4
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2answers
82 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
77 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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2answers
240 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. ...
3
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2answers
98 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
23 views

What is the difference between Problem Modelling and Problem Representation?

As I know, with problem representation is meant the formulation of the problem in a way that it can be programmed and therefore solved (for ex. you can represent the n-queens problem by using an array ...
3
votes
1answer
280 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 ...
3
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1answer
81 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
145 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
819 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
votes
1answer
89 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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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?
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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0answers
132 views

How can I convert the problem formulation to multi-agent reinforcement learning?

I'm trying to minimize the power consumption in wireless networks and I have some constraints such as that the SINR should not pass the threshold and the power should be between the 0 and maximum ...
2
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1answer
471 views

How does an unsupervised learning model learn?

How does an unsupervised learning model learn, if it does not involve any target values?
2
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1answer
60 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
votes
2answers
91 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
votes
2answers
203 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
22 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
20 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
votes
1answer
43 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
votes
2answers
472 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
votes
3answers
91 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
41 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
163 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
votes
1answer
132 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
vote
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.
1
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1answer
45 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
vote
2answers
108 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
vote
1answer
25 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 ...
1
vote
1answer
13 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 ...
1
vote
1answer
39 views

How do I normalise/un-normalise data when loading a model?

I am following this TensorFlow JS tutorial where you load car data. The data looks like this: [{x:100, y:20}, {x:80, y:33}] X is the horsepower of a car, Y is ...
1
vote
1answer
45 views

How to predict human future location?

I have billions of anonymized location coordinates of people movement collected from app. I want to improve user experience by using location data. For example identify if user is at home or at ...
1
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2answers
177 views

Why do we need a model of the environment in Dyna?

In chapter 8 of "Reinforcement Learning: An Introduction" by Sutton and Barto, it is stated that Dyna needs a model to simulate the environment. But why do we need a model? Why can't we just use the ...
1
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1answer
27 views

Is “dataset size” and “model size” same thing?

I mean what is determine my model size, connection amount between layers and neurons, or size of my dataset?
1
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1answer
36 views

Are there any advantages of using rules-based approaches versus models for detecting spam?

Suppose that we have unlabeled data. That is, all we have are a collection of emails and want to determine whether any of them is spam or not. Let's say we have $1,000$ rules to determine whether a ...
1
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0answers
31 views

What is meant by “model discriminability for local patches within the receptive field”?

In the Abstract section of the paper Network In Network, what does the authors actually mean to say?
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0answers
18 views

How to handle Feature changes in a model deployed ?

I implemented and deployed with Flask an XGBoost model for a classification problem. But being aware that features importance can change over time to predict probability of label for new data, I ...