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 regarding action recognition. This should be used when asking about what could be implemented that complements or harms this.
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For questions related to incremental learning algorithms, which are algorithms that attempt to learn new information without forgetting all the previously learned one. Incremental learning is often a …
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For questions related to the reinforcement learning algorithm called Deep Deterministic Policy Gradient (DDPG).
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For questions related to the framework called "Gym".
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For questions related to the book "Artificial Intelligence: A Modern Approach" by Peter Norvig and Stuart J. Russell.
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For questions related to off-policy reinforcement learning algorithms, which estimate a policy (the target policy) while using another policy (the behavior policy), during the learning process, which …
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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 …
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For questions related to deepfakes, which refers to machine learning techniques used to combine and superimpose existing images and videos onto source images or videos. Deepfakes have been used to cre…
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For question about artificial systems that exhibit the behavioral characteristics of natural living systems.
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For questions related to forecasting of any type beyond basic forms of extrapolation, as applicable in fields such as financial planning, portfolio management tooling, automated driving or piloting co…
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For questions related to explainable artificial intelligence (XAI), also known as interpretable AI, which refers to AI techniques that can be trusted and easily understood by humans, which are particu…
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Use for pathfinding, pathing, plotting, etc.
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Use for questions involving fitness functions.
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For questions about the use/aspects/implementation/intuition/mathematical proofs of various Linear Algebra methods used in Machine Learning and AI algorithms.
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For questions about the proofs/intuitions/methods of combinatorial mathematics used in an AI algorithm.
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For questions about implementation of Machine Learning and Artificial Intelligence algorithms in the C++ programming language.
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For questions about the application of Artificially Intelligent agents and Machine Learning Algorithms in the healthcare industry.
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knowledge about the real world. Humans have implicit knowledge of the real world, but an AI needs to have explicit resources to explain how the real world works. Use this tag for qu…
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For questions related to the ant colony optimization (ACO) algorithms, which are population-based and stochastic metaheuristics that can be used to find approximate solutions to difficult optimization…
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For questions related to the random forest (or random decision forests), which is an ensemble machine learning technique (that is, an ML technique that uses or combines different models).
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For questions related to control theory and its relation to reinforcement learning and other artificial intelligence sub-fields.
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For questions related to clustering (a usual unsupervised learning technique).
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For questions related to anomaly detection (or outlier detection) algorithms, which is the identification of rare items, events or observations which raise suspicions by differing significantly from t…
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For questions related to the concept of value (or performance, or quality, or utility) function (as defined in reinforcement learning and other AI sub-fields). An example of this type of functions is …
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For questions related to Bayesian networks, which are e.g. used to study causality (or causation) in AI.
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The process of discovering patterns in large data sets by AI.
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For questions related to variational auto-encoders (VAEs). The first VAE was proposed in "Auto-Encoding Variational Bayes" (2013) by Diederik P. Kingma and Max Welling. There are several other VAEs, f…
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For questions related to admissible heuristics, which are heuristics that never overestimate the cost of reaching a goal.
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For questions related to GPT (which stands for Generative Pre-Training), which is a combination of transformers (proposed in "Attention is All You Need") and unsupervised pre-training for solving lang…
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Partially Observable Markov Decision Process
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For questions related to greedy searches and greedy state-action strategies in that they prioritize or focus on the acquisition of more near term rewards than the mapping of plans to outcomes to achie…
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For questions related to the "on-policy" reinforcement learning algorithms.
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For questions related to teaching and learning AI concepts.