Questions tagged [definitions]
For questions about the definition of terms used in artificial intelligence research and development, including the definition of intelligence, algorithms, jargon, principles, methodologies, mathematical terms, concepts, topologies, architectures, designs, jargon, and AI domains such as robotics, network training, or automated vehicles.
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What is the fundamental difference between an ML model and a function?
A model can be roughly defined as any design that is able to solve an ML task. Examples of models are the neural network, decision tree, Markov network, etc.
A function can be defined as a set of ...
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What is machine learning?
What is the definition of machine learning? What are the advantages of machine learning?
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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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What are the minimum requirements to call something AI?
I believe artificial intelligence (AI) term is overused nowadays. For example, people see that something is self-moving and they call it AI, even if it's on autopilot (like cars or planes) or there is ...
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What is the difference between tree search and graph search?
I have read various answers to this question at different places, but I am still missing something.
What I have understood is that a graph search holds a closed list, with all expanded nodes, so ...
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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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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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What is a probability distribution in machine learning?
If we were learning or working in the machine learning field, then we frequently come across the term "probability distribution". I know what probability, conditional probability, and ...
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How can one distinguish between an AI and a "sufficiently advanced algorithm"?
Any sufficiently advanced algorithm is indistinguishable from AI.---Michael Paulukonis
According to What are the minimum requirements to call something AI?, there are certain requirements that a ...
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What is the credit assignment problem?
In reinforcement learning (RL), the credit assignment problem (CAP) seems to be an important problem. What is the CAP? Why is it relevant to RL?
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What is a graph neural network?
What is a graph neural network (GNN)?
Here are some sub-questions
How is a GNN different from a NN?
How exactly is a GNN related to graphs?
What are the components of a GNN? What are the inputs and ...
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What is a convolutional neural network?
Given that this question has not yet been asked on this site, although similar questions have already been asked in the past (e.g. here or here), what is essentially a convolutional neural network (...
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What is the most general definition of "intelligence"?
When we talk about artificial intelligence, human intelligence, or any other form of intelligence, what do we mean by the term intelligence in a general sense? What would you call intelligent and what ...
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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 AlphaZero an example of an AGI?
From DeepMind's research paper on arxiv.org:
In this paper, we apply a similar but fully generic algorithm, which
we call AlphaZero, to the games of chess and shogi as well as Go,
without any ...
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What does "death" intuitively mean in the paper "Death and Suicide in Universal Artificial Intelligence"?
In the paper Death and Suicide in Universal Artificial Intelligence, a proposal is given for what death could mean for Artificial Intelligence.
What does this mean using English only? I understand ...
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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 non-Euclidean data?
What is non-Euclidean data?
Here are some sub-questions
Where does this type of data arise? I have come across this term in the context of geometric deep learning and graph neural networks.
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Why can't OCR be perceived as a good example of AI?
On the Wikipedia page about AI, we can read:
Optical character recognition is no longer perceived as an exemplar of "artificial intelligence" having become a routine technology.
On the other hand, ...
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What is a recurrent neural network?
Surprisingly, this wasn't asked before - at least I didn't find anything besides some vaguely related questions.
So, what is a recurrent neural network, and what are their advantages over regular (or ...
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What are hyper-heuristics, and how are they different from meta-heuristics?
I wanted to know what the differences between hyper-heuristics and meta-heuristics are, and what their main applications are. Which problems are suited to be solved by hyper-heuristics?
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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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Why does the definition of the reward function $r(s, a, s')$ involve the term $p(s' \mid s, a)$?
Sutton and Barto define the state–action–next-state reward function, $r(s, a, s')$, as follows (equation 3.6, p. 49)
$$
r(s, a, s^{\prime}) \doteq \mathbb{E}\left[R_{t} \mid S_{t-1}=s, A_{t-1}=a, S_{t}...
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If expert systems are a bunch of if-then-else statements, then how are they termed as AI?
An artificial intelligence (AI) is often defined as something that can learn over time and can imitate human behaviors.
If an Expert system (e.g. MYCIN) that only involves if-then-else statements ...
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How are afterstate value functions mathematically defined?
In this answer, afterstate value functions are mentioned, and that temporal-difference (TD) and Monte Carlo (MC) methods can also use these value functions. Mathematically, how are these value ...
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What is teacher forcing?
In the paper Neural Programmer-Interpreters, the authors use the teacher forcing technique, but what exactly is it?
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What is the concept of the technological singularity?
I've heard the idea of the technological singularity, what is it and how does it relate to Artificial Intelligence? Is this the theoretical point where Artificial Intelligence machines have progressed ...
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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 are ontologies in AI?
What exactly are ontologies in AI? How should I write them and why are they important?
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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 is the difference between search and planning?
I'm reading the book Artificial Intelligence: A Modern Approach (by Stuart Russell and Peter Norvig).
However, I don't understand the difference between search and planning. I was more confused when I ...
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What are some examples of intelligent agents for each intelligent agent class?
There are several classes of intelligent agents, such as:
simple reflex agents
model-based reflex agents
goal-based agents
utility-based agents
learning agents
Each of these agents behaves slightly ...
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Are humans intelligent according to the definition of an intelligent agent?
Given the following definition of an intelligent agent (taken from a Wikipedia article)
If an agent acts so as to maximize the expected value of a performance measure based on past experience and ...
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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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What is a trap function in the context of a genetic algorithm?
What is a trap function in the context of a genetic algorithm? How is it related to the concepts of local and global optima?
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What is eager learning and lazy learning?
What is the difference between eager learning and lazy learning?
How does eager learning or lazy learning help me build a neural network system? And how can I use it for any target function?
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How do we express $q_\pi(s,a)$ as a function of $p(s',r|s,a)$ and $v_\pi(s)$?
The task (exercise 3.13 in the RL book by Sutton and Barto) is to express $q_\pi(s,a)$ as a function of $p(s',r|s,a)$ and $v_\pi(s)$.
$q_\pi(s,a)$ is the action-value function, that states how good ...
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How to define machine learning to cover clustering, classification, and regression?
How to define machine learning to cover clustering, classification, and regression? What unites these problems?
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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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Why do we commonly use the $\log$ to squash frequencies?
Term frequency and inverse document frequency are well-known terms in information retrieval.
I am presenting the definitions for both from p:12,13 of Vector Semantics and Embeddings
On term frequency
...
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Does self-supervised learning require auxiliary tasks?
Self-supervised learning algorithms provide labels automatically. But, it is not clear what else is required for an algorithm to fall under the category "self-supervised":
Some say, self-...
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What is generalized policy iteration?
I am reading Sutton and Barto's material now. I know value iteration, which is an iterative algorithm taking the maximum value of adjacent states, and policy iteration. But what is generalized policy ...
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What does the Markov assumption say about the history of state sequences?
Does the Markov assumption say that the conditional probability of the next state only depends on the current state or does it say that the conditional probability depends on a fixed finite number of ...
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How to define the "Pre-Processing" in machine learning?
Is every process (such as data acquisition, splitting the data for validation, data cleaning, or feature engineering) that is done on the data before we train the model always called the pre-...
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What are preferences and preference functions in multi-objective reinforcement learning?
In RL (reinforcement learning) or MARL (multi-agent reinforcement learning), we have the usual tuple:
(state, action, transition_probabilities, reward, next_state)
...
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What is the difference between artificial neural networks and deep learning?
I have read many mixed definitions around these two terms. For example, is it right to say deep learning is any ANN with more than two hidden layers?
What are formal definitions for these two?
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Is it okay to think of any dataset in artificial intelligence as a mathematical set?
A dataset is a collection of data points. It is known that the data points in the dataset can repeat. And the repetition does matter for building AI models.
So, why does the word dataset contain the ...
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What is the formal definition for manifold in artificial intelligence?
We come across the word "manifold" in artificial intelligence, especially in the domains where learning is done based on data instances.
What is the formal definition for manifold?
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