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.
For questions about the 1d convolution in convolutional neural networks.
For questions related to the 8-puzzle problem (or game). There are variations of this game with more titles, such as the 15-puzzle problem (also known as Game of Fifteen).
For questions related to the eight queens problem (or puzzle) in the context of artificial intelligence.
For questions related to the asynchronous advantage actor-critic (A3C) algorithm.
For questions related to the academic aspects of AI, and the academic fields involving AI.
For questions related to the accuracy metric/measure, which is the number of correct predictions divided by the total number of predictions.
For questions related to the "action model learning", which is an area of machine learning concerned with creation and modification of software agent's knowledge about effects and preconditions of the…
For questions regarding action recognition. This should be used when asking about what could be implemented that complements or harms this.
For questions about action spaces in the context of reinforcement learning and other AI sub-fields.
For questions related to the selection of and theory behind specific activation functions used in artificial networks.
For questions related to active learning, which is a machine learning technique where the user is interactively queried to label certain unlabelled training examples.
For questions related to the family of reinforcement learning algorithms denoted by "actor-critic", where there is an actor (a policy) and a critic (a value function).
For questions about the ADADELTA optimization algorithm used to train neural networks. ADADELTA adaptively changes the learning rate during training. It was proposed in the paper "ADADELTA: An Adaptiv…
For questions about Adam, a gradient-based optimization algorithm widely used to train neural networks. It was proposed in the paper "Adam: A Method for Stochastic Optimization" (2014) by Diederik P. …
For questions related to admissible heuristics, which are heuristics that never overestimate the cost of reaching a goal.
For questions related to the advantage actor-critic algorithms (that is, actor-critic algorithms that use the "advantage" function).
For questions about the concept of an adversarial attack in machine learning.
For questions related to adversarial machine learning, which is a branch of machine learning focused on the study of adversarial examples, which are malicious inputs designed to fool machine learning …
For questions related to the adversarial search problem (where there is more than one agent and the goals of these agents are in conflict) and algorithms to solve it (such as minimax).
For questions related to Auto-Encoding Variational Bayes (AEVB) algorithm, which was proposed in the paper "Auto-Encoding Variational Bayes" (by Diederik P Kingma and Max Welling, 2013), which also in…
For questions related to affective computing, which is the study and development of systems and devices that can recognize, interpret, process, and simulate human emotions (or affects). AC is an inter…
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…
Use for basic, fundamental questions about AI theory or practice. (i.e. design, application, implementation, mathematics of AI, philosophy of AI, etc.)