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A deterministic finite automaton M is a 5- tuple, (Q, Σ, δ, q0, F), consisting of. a finite set of states Q. a finite set of input symbols called the alphabet Σ. a transition function δ: Q × Σ → Q. an initial or start state q 0 ∈ Q {\displaystyle q_ {0}\in Q} a set of accept states F ⊆ Q {\displaystyle F\subseteq Q}
The Rete algorithm (/ ˈriːtiː / REE-tee, / ˈreɪtiː / RAY-tee, rarely / ˈriːt / REET, / rɛˈteɪ / reh-TAY) is a pattern matching algorithm for implementing rule-based systems. The algorithm was developed to efficiently apply many rules or patterns to many objects, or facts, in a knowledge base. It is used to determine which of the ...
Internet traffic. Internet traffic is the flow of data within the entire Internet, or in certain network links of its constituent networks. Common traffic measurements are total volume, in units of multiples of the byte, or as transmission rates in bytes per certain time units. As the topology of the Internet is not hierarchical, no single ...
A partially observable Markov decision process (POMDP) is a generalization of a Markov decision process (MDP). A POMDP models an agent decision process in which it is assumed that the system dynamics are determined by an MDP, but the agent cannot directly observe the underlying state. Instead, it must maintain a sensor model (the probability ...
In machine learning, a hyperparameter is a parameter that can be set in order to define any configurable part of a model's learning process. Hyperparameters can be classified as either model hyperparameters (such as the topology and size of a neural network) or algorithm hyperparameters (such as the learning rate and the batch size of an optimizer).
Neural networks based artificial intelligence and fuzzy logic are, when analyzed, the same thing—the underlying logic of neural networks is fuzzy. A neural network will take a variety of valued inputs, give them different weights in relation to each other, combine intermediate values a certain number of times, and arrive at a decision with a ...
Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [ 1 ][ 2 ] It learns to represent text as a sequence of vectors using self-supervised learning. It uses the encoder-only transformer architecture. It is notable for its dramatic improvement over previous state ...
Connectivism. Connectivism is a theoretical framework for understanding learning in a digital age. It emphasizes how internet technologies such as web browsers, search engines, wikis, online discussion forums, and social networks contributed to new avenues of learning. Technologies have enabled people to learn and share information across the ...