Questions tagged [terminology]

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

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7
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2answers
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Do GANs come under supervised learning or unsupervised learning?

Do GANs come under supervised learning or unsupervised learning? My guess is that they come under supervised learning, as we have labeled dataset of images, but I am not sure as there might be other ...
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What is a learning agent?

What is a learning agent, and how does it work? What are examples of learning agents (e.g., in the field of robotics)?
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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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1answer
3k views

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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3answers
579 views

What is the name of an AI system that learns by trial and error?

Imagine a system that controls dampers in a complex vent system that has an objective to perfectly equalize the output from each vent. The system has sensors for damper position, flow at various ...
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1answer
43 views

What are “function terms” in the context of an ontology?

I was going through the Wikipedia page on ontology components and noticed something that I had been hoping to find, for a long time. In the components' overview it mentioned: Function terms: ...
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What is artificial intelligence?

What is the definition of artificial intelligence?
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1answer
57 views

Differences between an agent that thinks rationally and an agent that acts rationally?

Stuart Russell and Peter Norvig pointed out 4 four possible goals to pursue in artificial intelligence: systems that think/act humanly/rationally. What are the differences between an agent that ...
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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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1answer
393 views

What is the relation between an environment, a state and a model?

In particular, I would like to have a simple definition of "environment" and "state". What are the differences between those two concepts? Also, I would like to know how the concept of model relates ...
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497 views

In what ways is the term “topology” applied to Artificial Intelligence?

I have a 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 topological ...
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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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3answers
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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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1answer
449 views

What is the difference between policy and action in reinforcement learning?

I'm confused with the two terminology - action and policy - in Reinforcement Learning. As far as I know, the action is: It is what the agent makes in a given state. However, the book I'm reading ...
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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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1answer
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Are iterative deepening, principal variation search or quiescence search extensions of alpha-beta pruning?

I know that there are several optimizations for alpha-beta pruning. For example, I have come across iterative deepening, principal variation search, or quiescence search. However, I am a little bit ...
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What is feature embedding in the context of convolutional neural networks?

What are feature embeddings in the context of convolutional neural networks? Is it related to bottleneck features or feature vectors?
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1answer
99 views

Is it a valid Deep Neural Network?

For a regression task, I have sequences of training data and if I define the layers of deep neural network to be: Layers=[ sequenceInputLayer(featuredimension) reluLayer dropoutLayer(0.05) ...
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710 views

What is the difference between on and off-policy deterministic actor-critic?

In the paper Deterministic Policy Gradient Algorithms, I am really confused about chapter 4.1 and 4.2 which is "On and off-policy Deterministic Actor-Critic". I don't know what's the difference ...
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3answers
669 views

Intelligence vs. Rationality?

This just popped into my head, and I haven't thought it through, but it feels like a sound question. The definition of intelligence might still be somewhat fuzzy, possibly a factor of our evolving ...
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1answer
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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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1answer
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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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1answer
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Neural Network Cell (Node) Types

I found this nice-ish-looking diagram, but it has a wholly inadequate descriptions for each of the cell types, aside from including names. What is the definition/description of each of these cell ...
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2answers
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Why do we need learning in unsupervised learning? [duplicate]

I am not clear with the concept that an unsupervised model learns. We are giving an input and output to the supervised model, so that it can generate a particular value, pattern or something out of it ...
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6answers
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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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1answer
159 views

What is a weighted average in a non-stationary k-armed bandit problem?

In the book Reinforcement Learning: An Introduction (page 25), by Richard S. Sutton and Andrew G. Barto, there is a discussion of the k-armed bandit problem, where the expected reward from the bandits ...
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What is the concept of Tensorflow Bottlenecks?

What is the concept and how does one calculate Bottleneck values? How do these values help image classification? Please explain in simple words.
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What are different approaches used in Machine Learning?

There seem to be so many sub-fields, so I'm interested in getting a better understanding of the approaches. I'm looking for information on a single framework per answer, in order to allow for ...
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1answer
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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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What other kind of AIs exist apart from goal-driven?

Goal-driven AIs is the only kind of AI I am aware of. However, Marcus Hutter claims the following Most, if not all known facets of intelligence can be formulated as goal driven or, more generally, ...
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1answer
69 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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1answer
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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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3answers
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Does any Math/Algos actually mimic human intelligence?

I've been reading about AI/Deep Learning, etc. to understand robots (i.e. Elon Musk warning). But I must be missing something... Can the entire field be summed-up in this one sentence? "Neural ...
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1answer
77 views

Biological analogy for boosting and inhibition idea in Hierarchical Temporal Memory (HTM)

I've just watched the 9th episode of HTM school about the "boosting" and "inhibition" ideas. However, I couldn't find the neuroscience counterpart of these terms and concepts. Since HTM is a ...
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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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6answers
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Is transistor the first artificial intelligence?

Artificial Intelligence is any device that perceives its environment and takes actions that maximize its chance of success at some goal. I got this definition from Wikipedia that cited "Russell and ...
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What is the difference between assisted and unassisted learning in relation to AI?

Is this related to supervised and unsupervised machine learning? Is it related to AI assisted human learning, and what is the distinction? Also, why is assisted machine learning seen as an ...
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1answer
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What is USV In NLP?

3 SVD Based Methods For this class of methods to find word embeddings (otherwise known as word vectors), we first loop over a massive data set and accumulate word co-occurrence counts in some form of ...
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2answers
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Is AI entirely a part of Computer Science?

Both AI and Computer Science are Sciences, as I understood from Wikipedia, Computer Science is everything that has any relation to computers. And AI is commonly defined as Study of machines that ...
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1answer
433 views

What is a state in a recurrent neural network?

I am Reading "Supervised Sequence Labelling with Recurrent Neural Networks" written by Alex Graves to try to understand LSTM networks and I am a bit confused about the equations. Specifically, what I ...
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3answers
362 views

What is meant by “known” in “A knowledge-base exhibits complete knowledge iff for every P (within its vocabulary) P or ~P is known”

I have a question as to what it means for a knowledge-base to be consistent and complete. I've been looking into non-monotonic logic and different formalisms for it from the book "knowledge ...
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6answers
884 views

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 ...
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2answers
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What is difference between edge computing and federated learning?

I recently read about federated learning introduced by Google, but it seems to be like edge computing. What is the difference between edge computing and federated learning?
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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 machine learning approach based on human learning?

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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1answer
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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'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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1answer
231 views

“Goodness” of a position in an Evaluation Function?

The Wikipedia states that: "An evaluation function, also known as a heuristic evaluation function or static evaluation function, is a function used by game-playing programs to estimate the value or ...
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What exactly are the differences between semantic and lexical-semantic networks?

What exactly are the differences between semantic and lexical-semantic networks?