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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. These properties allow it to solve problems that require the processing of very large data sets.
Decentralized computing. Decentralized computing is the allocation of resources, both hardware and software, to each individual workstation, or office location. In contrast, centralized computing exists when the majority of functions are carried out, or obtained from a remote centralized location. Decentralized computing is a trend in modern ...
Decentralized application. A decentralised application (DApp,[1] dApp, [2] Dapp, or dapp) is an application that can operate autonomously, typically through the use of smart contracts, that run on a decentralized computing, blockchain or other distributed ledger system. [3] Like traditional applications, DApps provide some function or utility ...
Not to be confused with Decentralized computing. Distributed computing is a field of computer science that studies distributed systems, defined as computer systems whose inter-communicating components are located on different networked computers. [ 1 ][ 2 ] The components of a distributed system communicate and coordinate their actions by ...
e. Decentralization or decentralisation is the process by which the activities of an organization, particularly those related to planning and decision-making, are distributed or delegated away from a central, authoritative location or group and given to smaller factions within it.
His main research publications are in stochastic control (centralized and decentralized), scheduling and resource allocation in networks with strategic and non-strategic users, and fault diagnosis in discrete event systems. He is a Fellow of IEEE for contributions to the theory of decentralized information systems and stochastic control.
Federated learning (also known as collaborative learning) is a sub-field of machine learning focusing on settings in which multiple entities (often referred to as clients) collaboratively train a model while ensuring that their data remains decentralized. [1] This stands in contrast to machine learning settings in which data is centrally stored ...
Reservation station. A unified reservation station, also known as unified scheduler, is a decentralized feature of the microarchitecture of a CPU that allows for register renaming, and is used by the Tomasulo algorithm for dynamic instruction scheduling. [1][2] Reservation stations permit the CPU to fetch and re-use a data value as soon as it ...
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