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Task Analysis, Environment Modeling, and Simulation (TAEMS or TÆMS) is a problem domain independent modeling language used to describe the task structures and the problem-solving activities of intelligent agents in a multi-agent environment. [1] [2] The intelligent agent operates in environments where: responses by specific deadlines may be ...
Python's name is derived from the British comedy group Monty Python, whom Python creator Guido van Rossum enjoyed while developing the language. Monty Python references appear frequently in Python code and culture; [190] for example, the metasyntactic variables often used in Python literature are spam and eggs instead of the traditional foo and ...
Mako is a template library written in Python. Mako is an embedded Python (i.e. Python Server Page) language, which refines the familiar ideas of componentized layout and inheritance. The Mako template is used by Reddit. [4] It is the default template language included with the Pylons [5] and Pyramid [6] web frameworks.
Examples include playing games, and solving problems and puzzles etc. Ellis (2003) [5] defines a task as a work plan that involves a pragmatic processing of language, using the learners' existing language resources and attention to meaning, and resulting in the completion of an outcome which can be assessed for its communicative function. David ...
That is, after pre-training, BERT can be fine-tuned with fewer resources on smaller datasets to optimize its performance on specific tasks such as natural language inference and text classification, and sequence-to-sequence-based language generation tasks such as question answering and conversational response generation. [12]
Optimizing a model based on human feedback is desirable when a task is difficult to specify yet easy to judge. [6] For example, one may want to train a model to generate safe text that is both helpful and harmless (such as lacking bias, toxicity, or otherwise harmful content). Asking humans to manually create examples of harmless and harmful ...
Flow-based programming defines applications using the metaphor of a "data factory". It views an application not as a single, sequential process, which starts at a point in time, and then does one thing at a time until it is finished, but as a network of asynchronous processes communicating by means of streams of structured data chunks, called "information packets" (IPs).
A common exercise in learning how to build discrete-event simulations is to model a queueing system, such as customers arriving at a bank teller to be served by a clerk. In this example, the system objects are Customer and Teller, while the system events are Customer-Arrival, Service-Start and Service-End. Each of these events comes with its ...