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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.

3
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1answer
42 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 ...
6
votes
1answer
108 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 ...
3
votes
2answers
37 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-...
1
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0answers
17 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
16 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 ...
4
votes
1answer
71 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,...
0
votes
1answer
27 views

How to label “other” while labeling image for object detection/classification?

I want to train a model to recognize different category of food (example: rice, burger, apple, pizza, orange,... ) After the first training, I realized that the model is detecting other object as ...
3
votes
1answer
91 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?
1
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0answers
38 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 ...
3
votes
1answer
84 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. ...
2
votes
1answer
38 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. ...
1
vote
2answers
98 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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0answers
30 views

Data Interpretation technique

In the model generation, in machine learning (consider supervised) If some data change the previous model function drastically then we should study that data. Does it happen? How to handle such ...
1
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0answers
30 views

Abstracting parameters of dynamic model from output time series

I am unable to identify general temrs or specific source of information for the below proposed problem. I would appreciate if the community can guide me to journal articles/books and keywords to look ...
1
vote
2answers
309 views

Are mathematical models the answer to general artificial intelligence?

As someone who knows basics of machine learning, I have doubts that mathematical models are answer for general AI. I am not sure if it is possible to represent emotions, intuition, knowledge and so on ...
4
votes
3answers
131 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 ...
0
votes
6answers
831 views

difference between ai-architecture and ai-model?

What is the difference between AI architecture and AI models. Are both of them same? if not please distinguish both of them and give example of each. And also suggest books/ papers that delve on AI ...
2
votes
2answers
79 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 ...
1
vote
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
0answers
15 views

Should I be using a validation curve accuracy score in lieu of error bars for a model fit to time series data?

Normally when doing a fit to some time series data (e.g., a polynomial fit), functions will return an associated error with each fitted point. I'm now trying out scikit-learn's support vector ...
2
votes
0answers
127 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 ...
3
votes
2answers
581 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
2answers
89 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 ...
2
votes
3answers
82 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 ...
1
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0answers
40 views

Could you share your model of Intelligence and/or conciousness?

I'm wondering if anyone reading this has developed a flowchart type representation of Intelligence and/or consciousness. Some examples of theories would be the Three Stratum Theory of Intelligence, ...
6
votes
1answer
65 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 ...
2
votes
1answer
86 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 ...
2
votes
2answers
116 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.
3
votes
1answer
220 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
votes
2answers
5k views

Difference between agent function and agent program

What is the difference between agent function and agent program with respect to percept sequence? In the book "Artificial Intelligence: A modern approach", The agent function, notionally speaking, ...
3
votes
2answers
57 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 ...
1
vote
1answer
296 views

How does unsupervised learning model learn?

Unsupervised learning does not involve target values, so basically targets are most likely the same as the inputs (in other words, involves no target values). So how does this model learn?
1
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2answers
93 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, ...
15
votes
3answers
859 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, ...
9
votes
2answers
310 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 ...
3
votes
1answer
1k 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?