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Federated learning (also known as collaborative learning) is a machine learning technique in a setting where multiple entities (often called clients) collaboratively train a model while keeping their data decentralized, [1] rather than centrally stored.
Federated Enterprise Architecture is a collective set of organizational architectures (as defined by the enterprise scope), operating collaboratively within the concept of federalism, in which governance is divided between a central authority and constituent units balancing organizational autonomy with enterprise needs.
A learning community is a group of people who share common academic goals and attitudes and meet semi-regularly to collaborate on classwork. Such communities have become the template for a cohort-based, interdisciplinary approach to higher education. This may be based on an advanced kind of educational or 'pedagogical' design. [1]
Collaborative learning is a situation in which two or more people learn or attempt to learn something together. [1] Unlike individual learning, people engaged in collaborative learning capitalize on one another's resources and skills (asking one another for information, evaluating one another's ideas, monitoring one another's work, etc.).
Distributed Artificial Intelligence (DAI) is an approach to solving complex learning, planning, and decision-making problems. It is embarrassingly parallel , thus able to exploit large scale computation and spatial distribution of computing resources .
Double Q-learning [23] is an off-policy reinforcement learning algorithm, where a different policy is used for value evaluation than what is used to select the next action. In practice, two separate value functions Q A {\displaystyle Q^{A}} and Q B {\displaystyle Q^{B}} are trained in a mutually symmetric fashion using separate experiences.
Instructional design (ID), also known as instructional systems design and originally known as instructional systems development (ISD), is the practice of systematically designing, developing and delivering instructional materials and experiences, both digital and physical, in a consistent and reliable fashion toward an efficient, effective, appealing, engaging and inspiring acquisition of ...
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.