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 “semantic level”?

I am reading the paper Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction (2018) by Yunzhe Tao et al. In this paper, they use several times the expression "semantic ...
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1answer
3k views

What is the definition of each of these neural network cell 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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What is the difference between an agent function and an agent program?

What is the difference between an agent function and an agent program (with respect to the percept sequence)? In the book "Artificial Intelligence: A modern approach", The agent function, ...
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2answers
621 views

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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1answer
183 views

How do I recognise a bandit problem?

I'm having difficulty understanding the distinction between a bandit problem and a non-bandit problem. An example of the bandit problem is an agent playing $n$ slot machines with the goal of ...
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1answer
2k views

What is the difference between search and planning?

I'm studying Artificial Intelligence. A Modern Approach, Stuart Russell, Peter Norvig, specifically about search and planning arguments. I don't understand the difference between the two terms. I was ...
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130 views

Is an algorithm that is no longer actively learning an AI?

This question assumes a definition of AI based on machine learning, and was inspired by this fun Technology Review post: SOURCE: Is this AI? We drew you a flowchart to work it out (Karen Hao, MIT ...
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173 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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1k views

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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191 views

What is “Computational Linguistics”?

It's not clear to me whether or not someone whose work aims to improve an NLP system may be called a "Computational Linguist" even when she/he doesn't modify the algorithm directly by coding. Let's ...
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327 views

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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498 views

Does the “lowest layer” refer to the first or last layer of the neural network?

People sometimes use 1st layer, 2nd layer to refer to a specific layer in a neural net. Is the layer immediately follows the input layer called 1st layer? How about the lowest layer and highest layer?...
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196 views

What does end-to-end training mean?

In simple words, what does end-to-end training mean, in the context of deep learning?
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208 views

What is an artificial neural network?

What is an artificial neural network in artificial intelligence? It is apparently used to find patterns in data and it is loosely inspired by human neural networks.
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42 views

What is the difference between a problem representation and problem modelling?

As far as I know, a problem representation is the formulation of the problem in a way that it can be programmed and therefore solved (for example, you can represent the $N$-queens problem by using an ...
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108 views

What is the relation between a policy which is the solution to a MDP and a policy like $\epsilon$-greedy?

In the context of reinforcement learning, a policy, $\pi$, is often defined as a function from the space of states, $\mathcal{S}$, to the space of actions, $\mathcal{A}$, that is, $\pi : \mathcal{S} \...
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285 views

Is the word “pose” used correctly in the paper “Matrix Capsules with EM Routing”?

In traditional computer vision and computer graphics, the pose matrix is a $4 \times 4$ matrix of the form $$ \begin{bmatrix} r_{11} & r_{12} & r_{12} & t_{1} \\ r_{21} & r_{...
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2k views

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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701 views

Are Rationality and Intelligence distinct?

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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1k views

How can I understand this statement about RNNs and hidden layers?

In the lecture, there was a statement: Recurrent neural networks with multiple hidden layers are just a special case that has some of the hidden to hidden connections missing. I understand ...
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436 views

What is the difference between abstract, autonomous and virtual intelligent agents?

On Wikipedia, we can read about different type of intelligent agents: abstract intelligent agents (AIA), autonomous intelligent agents, virtual intelligent agent (IVA), which I've found on other ...
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438 views

What is the meaning of “stationarity of statistics” and “locality of pixel dependencies”?

I'm reading the ImageNet Classification with Deep Convolutional Neural Networks paper by Krizhevsky et al, and came across these lines in the Intro paragraph: Their (convolutional neural networks') ...
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492 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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865 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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77 views

Why does a Lipschitz continuous discriminator in GANs assure statistical boundedness?

I have been reading the paper which introduced spectral normalization in GANs. At some point the paper mentions the following: The machine learning community has been pointing out recently that ...
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622 views

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 used ...
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54 views

What are the exact meaning of “lower-order structure” and “higher-order structure” in this paper?

I recently read a paper on community detection in networks. In the paper EdMot: An Edge Enhancement Approach for Motif-aware Community Detection, the authors consider the "lower-order structure" of ...
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169 views

Why is the target called “target” in Monte Carlo and TD learning if it is not the true target?

I was going through Sutton's book and, using sample-based learning for estimating the expectations, we have this formula $$ \text{new estimate} = \text{old estimate} + \alpha(\text{target} - \text{old ...
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142 views

How can reinforcement learning be unsupervised learning if it uses deep learning?

I was watching a video in my online course where I'm learning about A.I. I am a very beginner in it. At one point in the course, the instructor says that reinforcement learning (RL) needs a deep ...
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1k views

What is a “surrogate model”?

In the following paragraph from the book Automated Machine Learning: Methods, Systems, Challenges (by Frank Hutter et al.) In this section we first give a brief introduction to Bayesian ...
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1answer
282 views

What do the words “coarse” and “fine” mean in the context of computer vision?

I was reading the well know paper Fully Convolutional Networks for Semantic Segmentation, and, throughout the whole paper, they talk use the term fine and coarse. I was wondering what they mean. The ...
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1answer
527 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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1answer
92 views

What are “proxy data sets” in machine learning?

The paper Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration uses the term "proxy data sets" in this way To develop DL ...
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1answer
1k views

What is the relation between online learning and on-policy algorithms?

In the context of RL, there is the notion of on-policy and off-policy algorithms. I roughly understand the difference between on-policy and off-policy algorithms. Moreover, in RL, there's also the ...
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632 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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2answers
576 views

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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1answer
50 views

What is the type of problem requiring to rate images on a scale?

I'm new to the topic, but I've used some off the shelf knowledge about computer vision for classifying images. For example, you can easily generate labels that can determine whether or not e.g. a ...
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1answer
682 views

What does 'democratizing AI' exactly mean?

In my AI literature research, I often notice authors use term 'democratizing AI', especially in the AutoML area. I think I have an idea of what this means, but I would like to ask you for some more ...
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1answer
172 views

Is there any difference between a control and an action in reinforcement learning?

There are reinforcement learning papers (e.g. Metacontrol for Adaptive Imagination-Based Optimization) that use (apparently, interchangeably) the term control or action to refer to the effect of the ...
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1answer
730 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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1answer
106 views

Are there any DeepQA-based computers other than Watson?

My understanding is that Watson is the name of the computer, and DeepQA is the name of the software or technology. They are both correlated. Are there any computers/technologies other than Watson ...
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187 views

What is the meaning of “exploration” in reinforcement and supervised learning?

While exploration is an integral part of reinforcement learning (RL), it does not pertain to supervised learning (SL) since the latter is already provided with the data set from the start. That said, ...
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62 views

What is the difference between artificial intelligence and swarm intelligence?

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine ...
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87 views

Why are the terms classification and prediction used as synonyms in the context of deep learning?

Why are the terms classification and prediction used as synonyms especially when it comes to deep learning? For example, a CNN predicts the handwritten digit. To me, a prediction is telling the next ...
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1answer
35 views

What is the difference between the concepts “known environment” and “deterministic environment”?

According to the book "Artificial Intelligence: A Modern Approach", "In a known environment, the outcomes (or outcome probabilities if the environment is stochastic) for all actions are given.", and ...
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1answer
520 views

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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1answer
108 views

What is the difference between image processing and computer vision?

What is the difference between image processing and computer vision? They are apparently both used in artificial intelligence.
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808 views

What is a bad local minimum in machine learning?

What is "bad local minima"? The following papers all mention this expression. Eliminating all bad Local Minima from Loss Landscapes without even adding an Extra Unit limination of All Bad Local ...
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800 views

What is the role of biology in AI?

Biology is used in AI terminology. What are the reasons? What does biology have to do with AI? For instance, why is the genetic algorithm used in AI? Does it fully belong to biology?
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996 views

What is the difference between pixel-based object recognition and feature-based object recognition?

From my understanding and text I found in research papers online : Pixel-based object recognition: neural networks are trained to locate individual objects based directly on pixel data. Feature-based ...