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Laboratory-based studies of multi-tasking indicate that one motivation for switching between tasks is to increase the time spent on the task that produces the most reward (Payne, Duggan & Neth, 2007). This reward could be progress towards an overall task goal, or it could simply be the opportunity to pursue a more interesting or fun activity.
Computer multitasking, the concurrent execution of multiple tasks (also known as processes) over a certain period of time Cooperative multitasking; Pre-emptive multitasking; Human multitasking, the apparent performance by an individual of handling more than one task at the same time
In non-interactive execution (batch processing), a task is a unit of execution within a job, [1] [2] with the task itself typically a process. The term "multitasking" primarily refers to the processing sense – multiple tasks executing at the same time – but has nuances of the work sense of multiple tasks being performed at the same time.
Multi-task optimization is a paradigm in the optimization literature that focuses on solving multiple self-contained tasks simultaneously. [ 1 ] [ 2 ] The paradigm has been inspired by the well-established concepts of transfer learning [ 3 ] and multi-task learning [ 4 ] in predictive analytics .
New tasks can interrupt already started ones before they finish, instead of waiting for them to end. As a result, a computer executes segments of multiple tasks in an interleaved manner, while the tasks share common processing resources such as central processing units (CPUs) and main memory. Multitasking automatically interrupts the running ...
The following examples are taken from the "Abstract Algebra" and "International Law" tasks, respectively. [3] The correct answers are marked in boldface: Find all c {\displaystyle c} in Z 3 {\displaystyle \mathbb {Z} _{3}} such that Z 3 [ x ] / ( x 2 + c ) {\displaystyle \mathbb {Z} _{3}[x]/(x^{2}+c)} is a field.
A thesaurus (pl.: thesauri or thesauruses), sometimes called a synonym dictionary or dictionary of synonyms, is a reference work which arranges words by their meanings (or in simpler terms, a book where one can find different words with similar meanings to other words), [1] [2] sometimes as a hierarchy of broader and narrower terms, sometimes simply as lists of synonyms and antonyms.
Multi-task learning (MTL) is a subfield of machine learning in which multiple learning tasks are solved at the same time, while exploiting commonalities and differences across tasks. This can result in improved learning efficiency and prediction accuracy for the task-specific models, when compared to training the models separately.