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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 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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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 (https://arxiv.org/pdf/...
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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 of humans in ...
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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" and "embedding space" occur in several contexts. ...
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What is the difference between Problem Modelling and Problem Representation?

As I know, with problem representation is meant the formulation of the problem in a way that it can be programmed and therefore solved (for ex. you can represent the n-queens problem by using an array ...
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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 function where the ...
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33 views

What are the differences between learning by analogy, inductive learning and explanation based learning?

I have heard of the concepts of learning by analogy (which is quite self-explanatory), inductive learning and explanation-based learning. I tried to learn about inductive learning and explanation-...
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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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55 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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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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102 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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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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What is meant by the research topic “Humanitarian AI”?

What exactly is meant by "humanitarian AI"? What research areas does this cover? AI in healthcare? Algorithmic fairness? Applications of AI for economic development? Can anyone provide links to ...
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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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0answers
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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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If AI can perceive, can it be sentient? [duplicate]

AI should be perceiving - I think. There are debates around the world about the intelligence of an Super-Intelligent AI. I'm curious whether AI can have sentience or not.
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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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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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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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279 views

What is the actual learning algorithm: back-propagation or gradient descent?

What is the actual learning algorithm: back-propagation or gradient descent (or, in general, the optimization algorithm)? I am reading through chapter 8 of Parallel Distributed Processing hand book ...
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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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Greedy best first Search Algorithm vs A* search Algorithm

Greedy best first search Algorithm take the history and then check value ans then reach to goal. In A* search Algorithm take history and also cost then calculate value then reach to goal. When we ...
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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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Can a brain be intelligent without a body?

A more formal implication of this question is whether intelligence requires a context. On Topic This question may have little value to the fields of data science or statistics, however it is of ...
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1answer
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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
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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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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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473 views

Artificial Intelligence and Computational Intelligence

Having analysed,reviewed quite a number of user questions inline with answers concerning AI,sometimes I understand nor take note that AI community does not try much to avoid the term computational ...
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1answer
3k views

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 ...
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1answer
160 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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2answers
503 views

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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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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2answers
278 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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485 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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Are recent advances in machine learning really “artificial” intelligence, or merely brute force and human design?

It sounds like people boast of something being "artificial" about machine learning when actually people boast that humans implemented algorithms like e.g. Monte Carlo Search (MCST) etc. I think the ...
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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 “fringe” in the context of search algorithms?

I encountered the algorithm below, which is the general tree search algorithm. ...
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807 views

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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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 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
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 ...
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4answers
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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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Applied probabilistically… What does probabilistically mean?

I'm new in genetic algorithms and 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, second paragraph said:...
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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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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
71 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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Terminology of deep learning: “continuous” or “dynamic”?

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 NN either only prior to its deployment or ...