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 related to the Caffe deep learning library.
For questions related to the concept of testing or evaluating machine learning models and algorithms.
For questions related to the minimum description length (MDL) principle, which is a formalization of Occam's razor in which the best hypothesis (a model and its parameters) for a given set of data is …
For questions about Real-time Strategy games, often used in AI research.
For questions about the "AI business", the industry of AI, and related subjects.
For questions involving economics and economic decision-making.
a project that aims to build an open source artificial intelligence framework.
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 related to the iterative deepening A* search algorithm.
For questions related to the "expectation-maximisation" (EM) algorithm (which is used in several contexts in AI).
For questions about the mathematical notion of satisfiability.
For questions related to the concept of "optimal policy" in reinforcement learning.
Refers to the "knapsack" or "rucksack" problem in combinatorial optimization.
For questions related to the acquisition of rules that describe conditions and consequences related to actions, objects, or complex behaviors with or without certainty metrics. This may be from constr…
For questions related to the use of AI for the control of the quality of software development, a design process, a manufacturing process, a physical process, or another product, service, system, or pr…
For questions about "cybernetic organisms" defined as an entity with both organic and biomechatronic body parts. For questions about physical integration of animal and machine, theoretical and actua…
a programming paradigm where the focus is on what must be accomplished, rather than how it is to be accomplished. Hence it is more about "declaring" than about implementing …
For questions related to fully connected layers (which are often used as the last layers of a convolutional neural network).