Concept

Implicit graph

Résumé
In the study of graph algorithms, an implicit graph representation (or more simply implicit graph) is a graph whose vertices or edges are not represented as explicit objects in a computer's memory, but rather are determined algorithmically from some other input, for example a computable function. The notion of an implicit graph is common in various search algorithms which are described in terms of graphs. In this context, an implicit graph may be defined as a set of rules to define all neighbors for any specified vertex. This type of implicit graph representation is analogous to an adjacency list, in that it provides easy access to the neighbors of each vertex. For instance, in searching for a solution to a puzzle such as Rubik's Cube, one may define an implicit graph in which each vertex represents one of the possible states of the cube, and each edge represents a move from one state to another. It is straightforward to generate the neighbors of any vertex by trying all possible moves in the puzzle and determining the states reached by each of these moves; however, an implicit representation is necessary, as the state space of Rubik's Cube is too large to allow an algorithm to list all of its states. In computational complexity theory, several complexity classes have been defined in connection with implicit graphs, defined as above by a rule or algorithm for listing the neighbors of a vertex. For instance, PPA is the class of problems in which one is given as input an undirected implicit graph (in which vertices are n-bit binary strings, with a polynomial time algorithm for listing the neighbors of any vertex) and a vertex of odd degree in the graph, and must find a second vertex of odd degree. By the handshaking lemma, such a vertex exists; finding one is a problem in NP, but the problems that can be defined in this way may not necessarily be NP-complete, as it is unknown whether PPA = NP. PPAD is an analogous class defined on implicit directed graphs that has attracted attention in algorithmic game theory because it contains the problem of computing a Nash equilibrium.
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