Questions tagged [terminology]

For questions related to the definition of and use of terminology in the context of Artificial Intelligence

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118 views

What are episodic and non-episodic domains in reinforcement learning?

I was reading about the temporal difference (TD) learning and I read that: TD handles continuing, non-episodic domains Assuming that continuing means non-terminating, what does non-episodic or ...
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2answers
679 views

What are the major differences between cost, loss, error, fitness, utility, objective, criterion functions?

I find the terms cost, loss, error, fitness, utility, objective, criterion functions to be interchangeable, but any kind of minor difference explained is appreciated.
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Is the definition of machine learning by Mitchell in his book “Machine Learning” valid?

The definition machine learning is as follows: A computer program is said to learn from experience E with respect to some task T and performance measure P, if its performance at task T, as ...
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1answer
71 views

Aren't scores in the Wasserstein GAN probabilities?

I am quite new to GAN and I am reading about WGAN vs DCGAN. Relating to the Wasserstein GAN (WGAN), I read here Instead of using a discriminator to classify or predict the probability of generated ...
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1answer
63 views

In the machine learning literature, what does it mean to say that something is “embedded” in some space?

In the machine learning literature, I often see it said that something is "embedded" in some space. For instance, that something is "embedded" in feature space, or that our data ...
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41 views

How is an architecture composed of a second model that validates the first one called in machine learning?

I have a mix of two deep models, as follows: if model A is YES --pass to B--> if model B is YES--> result = YES if model A is NO ---> result = NO So ...
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1answer
75 views

What is the difference between success rate and reward when dealing with binary and sparse rewards?

In OpenAI Gym "reward" is defined as: reward (float): amount of reward achieved by the previous action. The scale varies between environments, but the ...
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2answers
82 views

Describing the order of a tensor

When describing tensors of higher order I feel like there is an overloading of the term dimension as it may be used to describe the order of the tensor but also the dimensionality of the... "orders"? ...
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1answer
50 views

What is the prediction accuracy?

In simple words, what is the prediction accuracy? What is it based on? How does it help? When is it used?
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1answer
4k views

What is a successor function (in CSPs)?

In Constraint Satisfaction Problems (CSPs), a state is any data structure that supports a successor function, a heuristic function, and a goal test. In this context, what is a successor function?
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21 views

Where does the hierarchical reinforcement learning framework name “MAXQ” come from?

I've been researching different frameworks for hierarchical RL (mainly options, HAMs, and MAXQ) and noticed that both options and HAMs have names that relate to how they function. I can't seem to find ...
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49 views

What is meant by “arranging the final features of CNN in a grid” and how to do it?

In the paper What You Get Is What You See: A Visual Markup Decompiler, the authors have proposed a method to extract the features from the CNN and then arrange those extracted features in a grid to ...
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21 views

How do CNNs or RNNs “stack the feature of nodes by a specific order”?

I am trying to understand the following statement taken from the paper Graph Neural Networks: A Review of Methods and Applications (2019). Standard neural networks like CNNs and RNNs cannot handle ...
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315 views

What does “episodic training” mean?

I'm reading the book Hands-On Meta Learning with Python, and in Prototypical networks said: So, we use episodic training—for each episode, we randomly sample a few data points from each class in ...
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1answer
69 views

Are CNN, LSTM, GRU and transformer AGI or computational intelligence tools?

Will CNN, LSTM, GRU and transformer be better classified as Computational Intelligence (CI) tools or Artificial General Intelligence (AGI) tools? The term CI arose back when some codes like neural ...
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42 views

What role do distractors play in natural language processing?

I’m doing research on natural language processing (NLP). I’d like to put together my own model. However, I'm running into a concept I am not familiar with, namely, distractors. A google search does ...
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1answer
29 views

What does “class-level discriminative feature representation” mean in the paper “Semi-Supervised Deep Learning with Memory”?

I am reading the paper Semi-Supervised Deep Learning with Memory (2018) by Yanbei Chen et al. The topic is the classification of images using semi-supervised learning. The authors use a term on page ...
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90 views

How does Friend-or-Foe Q-learning intuitively work?

I read about Q-Learning and was reading about multi-agent environments. I tried to read the paper Friend-or-Foe Q-learning, but could not understand anything, except for a very vague idea. What does ...
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1answer
53 views

What is “dense” in DensePose?

I've recently come across an amazing work for human pose estimation: DensePose: Dense Human Pose Estimation In The Wild by Facebook. In this work, they have tackled the task of dense human pose ...
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391 views

What are the differences between Deepfakes, FaceSwap and Face2Face?

I've compared videos manipulated with three different automated face manipulation methods: Deepfakes, Face2Face, and FaceSwap. Surprisingly, I found the output videos quite different: Deepfakes and ...
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1answer
106 views

Why do we use the word “kernel” in the expression “Gaussian kernel”?

I've heard the expression "Gaussian kernel" in several contexts (e.g. in the kernel trick used in SVM). A Gaussian kernel usually refers to a Gaussian function (that is, a function similar to the ...
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38 views

Continuous-attractor neural network explanation

I am reading about CANN, however, I do not seem to grasp what it is. Maybe someone who has worked with it can explain it? I found out about it while reading about RatSLAM. I understand that it helps ...
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327 views

How Swarm Intelligence can empower Blockchain?

Are there examples of applications in blockchain consensus using swarm intelligence, as opposed to classical consensus mechanisms like PoW or PBFT? Please note that recent classical consensuses, ...
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1answer
84 views

Why is Information Filter called Information Filter?

We all know Information Filter is a dual representation of Kalman Filter. The main difference between Information Filter and Kalman Filter is the way the Gaussian belief is represented. In Kalman ...
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1answer
82 views

Is the traditional meaning of “strong AI” outmoded?

Traditionally, "strong AI" refers to Artificial General Intelligence, the human mind understood as an algorithm (Searle, Chinese Room) and Artificial Consciousness. But recent advances in Artificial ...
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288 views

What is machine learning?

What is the definition of machine learning? What are the advantages of machine learning?
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1k views

What is “planning” in the context of reinforcement learning, and how is it different from RL and SL?

This is an excerpt taken from Sutton and Barto (pg. 3): Another key feature of reinforcement learning is that it explicitly considers the whole problem of a goal-directed agent interacting with an ...
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1answer
72 views

What does “probabilistically” mean?

I'm reading the A. E. Eiben and J. E. Smith book Introduction to Evolutionary Computing (Springer 2003). On section 3.5 Recombination, page 47, the second paragraph said: Recombination operators ...
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184 views

Who first coined the term “artificial general intelligence”?

Similarly to the question Who first coined the term Artificial Intelligence?, who first coined the term "artificial general intelligence"?
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1answer
104 views

Is there a Hebb neural network?

Is there a Hebb neural network? What kind of functions can it implement? Or, are there multiple "Hebb networks", that is, neural networks that learn in a Hebbian fashion?
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1answer
160 views

What is a “learned policy” in Q-learning?

I am completing an assignment at the moment. One of the assignment questions asks how you identified the learned policy and how you obtained it. The question is a reinforcement learning question, and ...
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1answer
111 views

Confusion between function learned and the underlying distribution

Let us assume that I am working on a dataset of black and white dog images. Each image is of size $28 \times 28$. Now, I can say that I have a sample space $S$ of all possible images. And $p_{data}$ ...
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1answer
44 views

What is the reason for taking tuples as vectors rather than points?

Across the literature of artificial intelligence, especially machine learning, it is normal to treat the tuples of datasets as vectors. Although there is a convention to treat them as data points. ...
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2answers
57 views

What is meant by a multi-dimensional continuous action space?

In the context of Reinforcement Learning, what does it mean to have a multi-dimensional continuous action space? I came across the following in the COBRA Paper A method for learning a distribution ...
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1answer
2k views

What is an agent in Artificial Intelligence?

While studying artificial intelligence, I have often encountered the term "agent" (often autonomous, intelligent). For instance, in fields such as Reinforcement Learning, Multi-Agent Systems, Game ...
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1answer
404 views

What's the difference between a static AI and a dynamic AI?

I recently watched a YouTube video (sorry, can't remember the link) where (a very talented) someone created what they called a "static AI". Somewhere in the video they said something along the lines ...
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1answer
958 views

Is a linear activation function (in the output layer) equivalent to an identity function?

I have a simple question about the choice of activation function for the output layer in feed-forward neural networks. I have seen several codes where the choice of the activation function for the ...
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1answer
322 views

Is it standard to say that an evaluation function estimates the “goodness” of a position?

Wikipedia states that: An evaluation function, also known as a heuristic evaluation function or static evaluation function, is a function used by game-playing computer programs to estimate the value ...
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1answer
40 views

What is the smoothness assumption in SVMs?

In this research paper, we have the following claim the smoothness assumption that underlies many kernel methods such as Support Vector Machines (SVMs) does not hold for deep neural networks trained ...
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2answers
193 views

Is the Q value the same as the state-action pair value?

Am I right to say that the Q value of a particular state and action is the same as the state-action pair value of that same state and action?
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1answer
38 views

What is it called in AI when a program is designed to make “x in the style of y”?

Simplified: What is it called in AI when a program is designed to make "x in the style of y;" when it trains off of two types of sources in order to make a thing from source one, informed by features ...
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1answer
144 views

What is a landmark in computer vision?

I guess I understand the concept of face detection, a technique specifies the location of multiple objects in the image, and draws bounding boxes on the target. The question is related to the concept ...
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1answer
63 views

Are there names for neural networks with a well-defined layer or neuron characteristics?

Are there names for neural networks with a well-defined layer or neuron characteristics? For example, a matrix that has the same number of rows and columns is called a square matrix. Is there an ...
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1answer
60 views

Is the following statement about neural networks overclaimed?

Is the following statement about neural networks overclaimed? Neural networks are iterative methods that minimize a loss function defined on the output layer of neurons. I wrote this statement in ...
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2answers
271 views

What is the difference between a learning algorithm and a hypothesis?

What's the distinction between a learning algorithm $A$ and a hypothesis $f$? I'm looking for a few concrete examples, if possible. For example, would the decision tree and random forest be considered ...
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2answers
65 views

What is “Word Sense Disambiguation”?

I recently came across this article which cites a paper which apparently won outstanding paper in ACL 2019. The theme is that it solved a longstanding problem called Word Sense Disambiguation. What ...
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3answers
70 views

Is superintelligence a function of strength or a category?

Super comes from the Latin and means "above". University of Oxford philosopher Nick Bostrom defines superintelligence as "any intellect that greatly exceeds the cognitive performance ...
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1answer
145 views

How can I calculate the “mean best fitness” measure in genetic algorithms?

I've just started to learn genetic algorithms and I have found these measurements of runs that I don't understand: MBF: The mean best fitness measure (MBF) is the average of the best fitness values ...
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1answer
47 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 ...
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1answer
60 views

What are support values in a support vector machine?

I started reading up on SVM and very little is defined of what are support values. I reckon it's they are denoted as $\alpha$ in most formulations.