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In mathematics, particularly graph theory, and computer science, a directed acyclic graph (DAG) is a directed graph with no directed cycles. That is, it consists of vertices and edges (also called arcs ), with each edge directed from one vertex to another, such that following those directions will never form a closed loop.
A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). [1] While it is one of several forms of causal notation, causal networks are special cases of Bayesian ...
UML class diagram of a Graph (abstract data type) The basic operations provided by a graph data structure G usually include: [1] adjacent(G, x, y): tests whether there is an edge from the vertex x to the vertex y; neighbors(G, x): lists all vertices y such that there is an edge from the vertex x to the vertex y;
A data structure known as a hash table.. In computer science, a data structure is a data organization and storage format that is usually chosen for efficient access to data. [1] [2] [3] More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, [4] i.e., it is an algebraic structure about data.
ASGs are usually directed acyclic graphs (DAG), although in some applications graphs containing cycles [clarification needed] may be permitted. For example, a graph containing a cycle might be used to represent the recursive expressions that are commonly used in functional programming languages as non-looping iteration constructs.
This is a list of well-known data structures. For a wider list of terms, see list of terms relating to algorithms and data structures. For a comparison of running times for a subset of this list see comparison of data structures.
A propositional directed acyclic graph (PDAG) is a data structure that is used to represent a Boolean function. A Boolean function can be represented as a rooted, directed acyclic graph of the following form: Leaves are labeled with (true), (false), or a Boolean variable.
Applying these two concepts results in an efficient data structure and algorithms for the representation of sets and relations. [ 10 ] [ 11 ] By extending the sharing to several BDDs, i.e. one sub-graph is used by several BDDs, the data structure Shared Reduced Ordered Binary Decision Diagram is defined. [ 2 ]