Questions tagged [terminology]
For questions related to the definition of and use of terminology in the context of Artificial Intelligence
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What is the difference between artificial intelligence and machine learning?
These two terms seem to be related, especially in their application in computer science and software engineering.
Is one a subset of another?
Is one a tool used to build a system for the other?
What ...
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What is fuzzy logic?
I'm new to A.I. and I'd like to know in simple words, what is the fuzzy logic concept? How does it help, and when is it used?
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What is the difference between strong-AI and weak-AI?
I've heard the terms strong-AI and weak-AI used. Are these well defined terms or subjective ones? How are they generally defined?
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What is the difference between a convolutional neural network and a regular neural network?
I've seen these terms thrown around this site a lot, specifically in the tags convolutional-neural-networks and neural-networks.
I know that a neural network is a system based loosely on the human ...
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What is the purpose of an activation function in neural networks?
It is said that activation functions in neural networks help introduce non-linearity.
What does this mean?
What does non-linearity mean in this context?
How does the introduction of this non-...
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What is the difference between latent and embedding spaces?
In general, the word "latent" means "hidden" and "to embed" means "to incorporate". In machine learning, the expressions "hidden (or latent) space" ...
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How is a deep neural network different from other neural networks?
How is a neural network having the "deep" adjective actually distinguished from other similar networks?
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What is the "temperature" in the GPT models?
What does the temperature parameter mean when talking about the GPT models?
I know that a higher temperature value means more randomness, but I want to know how randomness is introduced.
Does ...
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What are "bottlenecks" in neural networks?
What are "bottlenecks" in the context of neural networks?
This term is mentioned, for example, in this TensorFlow article, which also uses the term "bottleneck values". How does ...
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How can an AI train itself if no one is telling it if its answer is correct or wrong?
I am a programmer but not in the field of AI. A question constantly confuses me is that how can an AI be trained if we human beings are not telling it its calculation is correct?
For example, news ...
user31556
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What is the Bellman operator in reinforcement learning?
In mathematics, the word operator can refer to several distinct but related concepts. An operator can be defined as a function between two vector spaces, it can be defined as a function where the ...
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What is the difference between reinforcement learning and optimal control?
Coming from a process (optimal) control background, I have begun studying the field of deep reinforcement learning.
Sutton & Barto (2015) state that
particularly important (to the writing of the ...
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What is the difference between actor-critic and advantage actor-critic?
I'm struggling to understand the difference between actor-critic and advantage actor-critic.
At least, I know they are different from asynchronous advantage actor-critic (A3C), as A3C adds an ...
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What is the difference between an observation and a state in reinforcement learning?
I'm studying reinforcement learning. It seems that "state" and "observation" mean exactly the same thing. They both capture the current state of the game.
Is there a difference between the two terms?...
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What is the difference between active learning and online learning?
The definitions for these two appear to be very similar, and frankly, I've been only using the term "active learning" the past couple of years. What is the actual difference between the two? ...
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What is the difference between a receptive field and a feature map?
In a CNN, the receptive field is the portion of the image used to compute the filter's output. But one filter's output (which is also called a "feature map") is the next filter's input.
What's the ...
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What is a "trajectory" in reinforcement learning?
I'm now learning about reinforcement learning, but I just found the word "trajectory" in this answer.
However, I'm not sure what it means. I read a few books on the Reinforcement Learning but none of ...
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What is the fringe in the context of search algorithms?
What is the fringe in the context of search algorithms?
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Why is it called Latent Vector?
I just learned about GAN and I'm a little bit confused about the naming of Latent Vector.
First, In my understanding, a definition of a latent variable is a random variable that can't be measured ...
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What does "stationary" mean in the context of reinforcement learning?
I think I've seen the expressions "stationary data", "stationary dynamics" and "stationary policy", among others, in the context of reinforcement learning. What does it mean? I think stationary policy ...
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Who first coined the term Artificial Intelligence?
Who first coined the term Artificial Intelligence? Is there a published research paper that first used that term?
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What is the difference between artificial intelligence and computational intelligence?
Having analyzed and reviewed a certain amount of articles and questions, apparently, the expression computational intelligence (CI) is not used consistently and it is still unclear the relationship ...
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Is a genetic algorithm an example of artificial intelligence?
Since human intelligence presumably is a function of a natural genetic algorithm in nature, is using a genetic algorithm in a computer an example of artificial intelligence? If not, how do they differ?...
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What are good alternatives to the expression "Artificial Intelligence"?
I read a really interesting article titled "Stop Calling it Artificial Intelligence" that made a compelling critique of the name "Artificial Intelligence".
The word intelligence is so broad that it's ...
user6698
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What are bottleneck features?
In the blog post Building powerful image classification models using very little data, bottleneck features are mentioned. What are the bottleneck features? Do they change with the architecture that is ...
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What is the definition of "soft label" and "hard label"?
In semi-supervised learning, there are hard labels and soft labels. Could someone tell me the meaning and definition of the two things?
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What is "backprop"?
What does "backprop" mean? Is the "backprop" term basically the same as "backpropagation" or does it have a different meaning?
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What algorithms are considered reinforcement learning algorithms?
What are the areas/algorithms that belong to reinforcement learning?
TD(0), Q-Learning and SARSA are all temporal-difference algorithms, which belong to the reinforcement learning area, but is there ...
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What is a deep neural network? [duplicate]
What is the definition of a deep neural network? Why are they so popular or important?
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What are the differences between an agent and a model?
In the context of Artificial Intelligence, sometimes people use the word "agent" and sometimes use the word "model" to refer to the output of the whole "AI-process". For ...
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What do you call a machine learning system that keeps on learning?
As I understand it from this video lecture, there are three types of deep learning:
Supervised
Unsupervised
Reinforcement
All these can serve to train a neural network either only prior to its ...
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What's the term for death by dissolving in AI?
What's the term (if such exists) for merging with AI (e.g. via neural lace) and becoming so diluted (e.g. 1:10000) that it effectively results in a death of the original self?
It's not quite "digital ...
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What are ontologies in AI?
What exactly are ontologies in AI? How should I write them and why are they important?
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Are Cellular Neural Networks one type of Neural Networks?
I am researching Cellular Neural Networks and have already read Chua's two articles (1988). In cellular neural networks, a cell is only in relation with its neighbors. So it is easy to use them for ...
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What is an activity vector in capsule neural networks?
I was reading the paper Dynamic Routing Between Capsules and didn't understand the term "activity vector" in the abstract.
A capsule is a group of neurons whose activity vector represents the ...
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Is REINFORCE the same as 'vanilla policy gradient'?
I don't know what people mean by 'vanilla policy gradient', but what comes to mind is REINFORCE, which is the simplest policy gradient algorithm I can think of. Is this an accurate statement?
By ...
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What is the difference between an episode, a trajectory and a rollout?
I often see the terms episode, trajectory, and rollout to refer to basically the same thing, a list of (state, action, rewards). Are there any concrete differences between the terms or can they be ...
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What is the difference between memetic algorithms and genetic algorithms?
What is the difference between memetic algorithms and genetic algorithms? Is an individual's lifetime a learning part of memetic algorithms?
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What are sim2sim, sim2real and real2real?
Recently, I always hear about the terms sim2sim, sim2real and real2real. Will anyone explain the meaning/motivation of these terms (in DL/RL research community)?
What are the challenges in this ...
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What is the difference between artificial intelligence and robots?
What is the difference between artificial intelligence and robots?
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What is the difference between the prediction and control problems in the context of Reinforcement Learning?
What is the difference between the prediction (value estimation) and control problems in reinforcement learning?
Are there scenarios in RL where the problem cannot be distinctly categorised into the ...
user9947
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What are the main algorithms used in computer vision?
Nowadays, CV has really achieved great performance in many different areas. However, it is not clear what a CV algorithm is.
What are some examples of CV algorithms that are commonly used nowadays and ...
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What is the name of a human-inspired machine learning approach?
I once came across a neural network being trained without back-propagation or genetic algorithms (or using any kind of data sets). It was based on how the human brain learns and adjusts its ...
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What is the relation between the context in contextual bandits and the state in reinforcement learning?
Conceptually, in general, how is the context being handled in contextual bandits (CB), compared to states in reinforcement learning (RL)?
Specifically, in RL, we can use a function approximator (e.g. ...
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What is convergence in machine learning?
I came across this answer on Quora, but it was pretty sparse. I'm looking for specific meanings in the context of machine learning, but also mathematical and economic notions of the term in general.
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What is the difference between an agent function and an agent program?
In section 2.4 (p. 46) of the book Artificial Intelligence: A modern approach (3rd edition), Russell and Norvig write
The job of AI is to design an agent program that implements the agent function — ...
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Is reinforcement learning using shallow neural networks still deep reinforcement learning?
Often times I see the term deep reinforcement learning to refer to RL algorithms that use neural networks, regardless of whether or not the networks are deep.
For example, PPO is often considered a ...
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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,...
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In what ways is the term "topology" applied to Artificial Intelligence?
I have only a general understanding of General Topology, and want to understand the scope of the term "topology" in relation to the field of Artificial Intelligence.
In what ways are ...
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