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Tags

A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.

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For questions related to the deep Q-network (DQN), which is a deep neural network (e.g. a convolutional neural network) trained with a variant of Q-learning. The expression was coined in the paper "Pl…
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For questions related to the concept of loss (or cost) function in the context of machine learning.
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For questions about algorithms that exhibit characteristics of evolution in that the structure, form, or processes of that which is evolving incrementally improves, either by DNA mutation and selectio…
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For questions surrounding gradient descent, a method for finding the optimum state of a parameterized function based on another function often called the loss or error function. It iteratively descen…
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For questions about Artificial General Intelligence (AGI), a hypothetical machine characteristic permitting it to learn any arbitrary intellectual ability up to the limits of the available computing r…
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For questions about AI that learns without being provided with a set of labels (expected answers) along with the set of input examples.
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For questions related to modelling external environment, functional models tuned through convergent methods such as artificial networks or fuzzy logic containers, loss models, semantic models, model-b…
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Use when requesting examples of research or links to research papers. For example, "Looking for published research about X" or "What are good examples of Y in research?".
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For questions about prediction of a certain quantitative or a qualitative value by an algorithm
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For questions about chat-bots. NOT for questions about how to program a chat-bot, as those kinds of questions are off-topic.
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For questions related to deep reinforcement learning (DRL), that is, RL combined with deep learning. More precisely, deep neural networks are used to represent e.g. value functions or policies.
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For questions related to generative adversarial networks (GANs), introduced in the paper Generative Adversarial Nets (2014) by J. Goodfellow et al. A GAN is composed of a discriminative model (D) and …
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automate vehicles, including the autonomous vehicles capabilities of automated piloting and air traffic control for aircraft and orbital and interplanetary vehicles, a…
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For questions related to strong AI, which is also known as artificial general intelligence (a hypothetical machine that exhibits behavior at least as general and flexible as humans do). In contrast to…
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should be used for questions about the MCTS algorithm (how/why it works, potential applications, enhancements, combinations with other algorithms, implementation, etc.)
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For questions related to the neuroevolution technique called NeuroEvolution of Augmenting Topologies (NEAT), introduced in the paper "Evolving Neural Networks through Augmenting Topologies" (2002) by …
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For questions related to the concept of (intelligent) agents in artificial intelligence.
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Use for questions related to the social impacts of AI.
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For questions about different learning algorithms used by a Machine Learning program to achieve its end goal.
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For questions related to the concept of generative machine learning models, such as the Restricted Boltzmann Machine (RBM), the Variational Autoencoder (VAE), and the Generative Adversarial Network (G…
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For asking about an aspect of the history of AI.
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For questions on ethical issues related to AI. Questions may be concrete, such as ethical/unethical applications, or metaphysical, such as "will automata develop their own ethics?"
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For questions on behavior/performance of algorithms designed to mimic human qualities, behaviors, etc.
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For questions about algorithms and concepts for the development or use of logical inference capabilities in computers or the use of logical inference to arrive at the most useful AI designs.
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For questions about what constitutes an artificial neuron and how artificial neurons can be utilized as part of a neural network.
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For questions about methods/intuitions/proofs/improvements in the knowledge representation in a problem to be solved by Artificially Intelligent agent.
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For question about recognition of patterns (generally sequence of values following a certain mathematical equation) of any physical quantity.
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Use for questions related to Data Science aspects of AI. Generally speaking, only basic Data Science questions should be asked on this Stack, ideally involving the fundamental concepts. For more adv…
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For questions about autoencoders, a type of unsupervised artificial network for learning efficient data codings.
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For questions related to the selection of and theory behind specific activation functions used in artificial networks.
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For questions related to the theory or application of linear regression.
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For questions and clarifications about the use of AI/ML algorithms in the field of robotics.
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For questions related to the openAI, including the Gym toolkit.
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For questions related to reinforcement learning algorithms often referred to as "policy gradients" (or "policy gradient algorithms"), which attempt to directly optimise a parameterised policy (without…
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For questions related to object detection (which includes e.g. human or face detection), whose goal is to locate a specific object in an image. Object detection is different from object recognition, w…
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For questions that ask about or call for proofs for specific assertions, whether they be proofs of theorems or corollaries, proofs of concept through working implementation, counter proofs, or counter…