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GRAPH REDUCTION-MACHINE

  • Graph reduction machine
  • Special-purpose computer

    A graph reduction machine is a special-purpose computer built to perform combinator calculations by graph reduction. Examples include the SKIM ("S-K-I

    Graph reduction machine

    Graph_reduction_machine

  • Graph reduction
  • Efficient version of non-strict evaluation

    In computer science, graph reduction implements an efficient version of non-strict evaluation, an evaluation strategy where the arguments to a function

    Graph reduction

    Graph_reduction

  • Directed acyclic graph
  • Directed graph with no directed cycles

    In mathematics, particularly graph theory, and computer science, a directed acyclic graph (DAG) is a directed graph with no directed cycles. That is, it

    Directed acyclic graph

    Directed acyclic graph

    Directed_acyclic_graph

  • Knowledge graph
  • Type of knowledge base

    machine learning, particularly in graph neural networks, representation learning, and machine learning, have broadened the scope of knowledge graphs beyond

    Knowledge graph

    Knowledge graph

    Knowledge_graph

  • Graph neural network
  • Class of artificial neural networks

    Graph neural networks (GNNs) are artificial neural networks designed for tasks whose inputs are graphs. Because graphs usually do not have a canonical

    Graph neural network

    Graph_neural_network

  • Combinatory logic
  • Logical formalism using combinators instead of variables

    Categorical abstract machine Combinatory categorial grammar Explicit substitution Fixed point combinator Graph reduction machine Lambda calculus and Cylindric

    Combinatory logic

    Combinatory_logic

  • Lennart Augustsson
  • Swedish computer scientist

    languages had been implemented via interpreted graph reduction. LML compiled to graph reduction machine (G-machine) code. Part of the development team at Epic

    Lennart Augustsson

    Lennart_Augustsson

  • Weisfeiler Leman graph isomorphism test
  • Heuristic test for graph isomorphism

    In graph theory, the Weisfeiler Leman graph isomorphism test is a heuristic test for the existence of an isomorphism between two graphs G and H. It is

    Weisfeiler Leman graph isomorphism test

    Weisfeiler_Leman_graph_isomorphism_test

  • John Darlington
  • British academic and author

    parallel machine design, the ALICE functional graph reduction machine (1985), a forerunner of the commercial ICL Goldrush parallel database machine (1992);

    John Darlington

    John Darlington

    John_Darlington

  • Nonlinear dimensionality reduction
  • Projection of data onto lower-dimensional manifolds

    dimensionality reduction, such as singular value decomposition and principal component analysis. High dimensional data can be hard for machines to work with

    Nonlinear dimensionality reduction

    Nonlinear dimensionality reduction

    Nonlinear_dimensionality_reduction

  • Signal-flow graph
  • Flow graph invented by Claude Shannon

    A signal-flow graph or signal-flowgraph (SFG), invented by Claude Shannon, but often called a Mason graph after Samuel Jefferson Mason who coined the

    Signal-flow graph

    Signal-flow_graph

  • Knowledge graph embedding
  • Dimensionality reduction of graph-based semantic data objects [machine learning task]

    learning, knowledge graph embedding (KGE), also called knowledge representation learning (KRL), or multi-relation learning, is a machine learning task of

    Knowledge graph embedding

    Knowledge graph embedding

    Knowledge_graph_embedding

  • Embedding (machine learning)
  • Representation learning technique

    Word2Vec), image embeddings for visual data, and knowledge graph embeddings for knowledge graphs, each tailored to tasks like NLP, computer vision, or recommendation

    Embedding (machine learning)

    Embedding_(machine_learning)

  • NP-completeness
  • Complexity class

    problem Dominating set problem Graph coloring problem Sudoku To the right is a diagram of some of the problems and the reductions typically used to prove their

    NP-completeness

    NP-completeness

    NP-completeness

  • Outline of machine learning
  • Overview of and topical guide to machine learning

    Low-density separation Graph-based methods Co-training Transduction Deep learning Deep belief networks Deep Boltzmann machines Deep Convolutional neural

    Outline of machine learning

    Outline_of_machine_learning

  • Machine learning
  • Subset of artificial intelligence

    detection Investment management Knowledge graph embedding Linguistics Machine learning control Machine perception Machine translation Material Engineering Marketing

    Machine learning

    Machine_learning

  • List of functional programming topics
  • combinator SKI combinator calculus B, C, K, W system SECD machine Graph reduction machine Sequent, sequent calculus Natural deduction Intuitionistic

    List of functional programming topics

    List_of_functional_programming_topics

  • Dependency graph
  • Directed graph representing dependencies

    the dependency graph is a graph G = ( S , T ) {\displaystyle G=(S,T)} with T ⊆ R {\displaystyle T\subseteq R} the transitive reduction of R. For example

    Dependency graph

    Dependency_graph

  • ♯P-completeness of 01-permanent
  • Mathematical proof about the permanent of matrices

    equivalent matrix whose entries are all powers of 2. The reduction can be expressed in terms of graphs equivalent to the matrices. Let G {\displaystyle G}

    ♯P-completeness of 01-permanent

    ♯P-completeness_of_01-permanent

  • Deterministic acyclic finite state automaton
  • Data structure representing a finite set of strings

    Word Graph or DAWG" – JohnPaul Adamovsky teaches how to construct a DAFSA using an array of integers (Archived 22 July 2022 at the Wayback Machine) "Caroline

    Deterministic acyclic finite state automaton

    Deterministic acyclic finite state automaton

    Deterministic_acyclic_finite_state_automaton

  • Counting problem (complexity)
  • Type of computational problem

    polynomial-time many-one counting reduction. This problem is equivalent to counting perfect matchings in a bipartite graph. Deciding whether perfect matchings

    Counting problem (complexity)

    Counting_problem_(complexity)

  • Graph isomorphism problem
  • Unsolved problem in computational complexity theory

    of problems with a polynomial-time Turing reduction to the graph isomorphism problem. If in fact the graph isomorphism problem is solvable in polynomial

    Graph isomorphism problem

    Graph isomorphism problem

    Graph_isomorphism_problem

  • Computational complexity theory
  • Inherent difficulty of computational problems

    is the following. The input is an arbitrary graph. The problem consists in deciding whether the given graph is connected or not. The formal language associated

    Computational complexity theory

    Computational_complexity_theory

  • Apache Spark
  • Open-source data analytics cluster computing framework

    Malak, Michael (14 June 2016). "Finding Graph Isomorphisms In GraphX And GraphFrames: Graph Processing vs. Graph Database". slideshare.net. sparksummit

    Apache Spark

    Apache Spark

    Apache_Spark

  • Dimensionality reduction
  • Process of reducing the number of random variables under consideration

    Dimensionality reduction, or dimension reduction, is the transformation of data from a high-dimensional space into a low-dimensional space so that the

    Dimensionality reduction

    Dimensionality_reduction

  • Cyclomatic complexity
  • Measure of the structural complexity of a software program

    Cyclomatic complexity is computed using the control-flow graph of the program. The nodes of the graph correspond to indivisible groups of commands of a program

    Cyclomatic complexity

    Cyclomatic_complexity

  • Graph partition
  • Subdivision of vertices into disjoint sets

    In mathematics, a graph partition is the reduction of a graph to a smaller graph by partitioning its set of nodes into mutually exclusive groups. Edges

    Graph partition

    Graph_partition

  • Graph coloring
  • Methodic assignment of colors to elements of a graph

    In graph theory, graph coloring is a methodic assignment of labels traditionally called "colors" to elements of a graph. The assignment is subject to certain

    Graph coloring

    Graph coloring

    Graph_coloring

  • Joseph Gerber
  • American inventor and businessman

    his early developments of graphical-numerical computing devices, data-reduction tools, and plotters. He was awarded America's National Medal of Technology

    Joseph Gerber

    Joseph_Gerber

  • St-connectivity
  • t in a directed graph, if t is reachable from s. Formally, the decision problem is given by PATH = {⟨D, s, t⟩ | D is a directed graph with a path from

    St-connectivity

    St-connectivity

    St-connectivity

  • ♯P-complete
  • Complexity class

    machine. The problem is #P-hard, meaning that every other problem in #P has a polynomial-time Turing reduction or polynomial-time counting reduction to

    ♯P-complete

    ♯P-complete

  • Parity P
  • accepting computation paths is odd. An example of a ⊕P problem is "does a given graph have an odd number of perfect matchings?" The class was defined by Papadimitriou

    Parity P

    Parity_P

  • Stochastic gradient descent
  • Optimization algorithm

    gradient descent Linear classifier Online machine learning Stochastic hill climbing Stochastic variance reduction ⊙ {\displaystyle \odot } denotes the element-wise

    Stochastic gradient descent

    Stochastic_gradient_descent

  • Topological sorting
  • Node ordering for directed acyclic graphs

    computer science, a topological sort or topological ordering of a directed graph is a linear ordering of its vertices such that for every directed edge (u

    Topological sorting

    Topological_sorting

  • Tensor (machine learning)
  • Concept in machine learning

    higher-level designs of machine learning in the form of tensor graphs. This leads to new architectures, such as tensor-graph convolutional networks (TGCN)

    Tensor (machine learning)

    Tensor_(machine_learning)

  • Component (graph theory)
  • Maximal subgraph whose vertices can reach each other

    In graph theory, a component of an undirected graph is a connected subgraph that is not part of any larger connected subgraph. The components of any graph

    Component (graph theory)

    Component (graph theory)

    Component_(graph_theory)

  • Restricted Boltzmann machine
  • Class of artificial neural network

    implies, RBMs are a variant of Boltzmann machines, with the restriction that their neurons must form a bipartite graph: a pair of nodes from each of the two

    Restricted Boltzmann machine

    Restricted Boltzmann machine

    Restricted_Boltzmann_machine

  • Spectral clustering
  • Clustering methods

    the graph. They also look at two approximation algorithms in the same paper. Spectral clustering has a long history. Spectral clustering as a machine learning

    Spectral clustering

    Spectral clustering

    Spectral_clustering

  • Duncan's taxonomy
  • Classification of computer architectures

    this, programs are represented as graphs of expressions, which are dynamically updated as reduction proceeds. Graph nodes may represent values, operations

    Duncan's taxonomy

    Duncan's_taxonomy

  • Finite-state machine
  • Mathematical model of computation

    given to the machine) and the outputs resulting from each input: The turnstile state machine can also be represented by a directed graph called a state

    Finite-state machine

    Finite-state machine

    Finite-state_machine

  • Feature learning
  • Set of learning techniques in machine learning

    machines (RBMs) are often used as a building block for multilayer learning architectures. An RBM can be represented by an undirected bipartite graph consisting

    Feature learning

    Feature learning

    Feature_learning

  • NL-complete
  • the problem of determining whether, given a directed graph G and two nodes s and t on that graph, there is a path from s to t. ST-connectivity can be

    NL-complete

    NL-complete

  • Lambda calculus
  • Mathematical-logic system based on functions

    graphs extended with letrec, to detect possibly infinite unwinding trees; 2) the representational calculus with β-reduction of scoped lambda graphs constitute

    Lambda calculus

    Lambda calculus

    Lambda_calculus

  • Nondeterministic constraint logic
  • Combinatorial reconfiguration problem

    max-degree 3 graphs. The reduction follows from QSAT and is outlined below. The above problem is PSPACE-Complete even if the constraint graph is planar,

    Nondeterministic constraint logic

    Nondeterministic_constraint_logic

  • Stratospheric aerosol injection
  • Type of solar radiation modification

    and North America since the 1980s, and more recently in China. These reductions have improved air quality but diminish the cooling influence of aerosols

    Stratospheric aerosol injection

    Stratospheric aerosol injection

    Stratospheric_aerosol_injection

  • Hypergraph
  • Generalization of graph theory

    hypergraph is a generalization of a graph in which an edge can join any number of vertices. In contrast, in an ordinary graph, an edge connects exactly two

    Hypergraph

    Hypergraph

    Hypergraph

  • Clean (programming language)
  • Functional programming language

    library. Computing is based on graph rewriting and reduction. Constants such as numbers are graphs and functions are graph rewriting formulas. This, combined

    Clean (programming language)

    Clean_(programming_language)

  • Subgraph isomorphism problem
  • Problem in theoretical computer science

    many-one reduction shows that subgraph isomorphism is also NP-complete. An alternative reduction from the Hamiltonian cycle problem translates a graph G which

    Subgraph isomorphism problem

    Subgraph isomorphism problem

    Subgraph_isomorphism_problem

  • NP-hardness
  • Complexity class

    Longest simple path Graph coloring; an application: register allocation in compilers Lists of problems Lists of unsolved problems Reduction (complexity) Unknowability

    NP-hardness

    NP-hardness

    NP-hardness

  • Attention (machine learning)
  • Machine learning technique

    Xiaolong (2018). Non-Local Neural Networks. CVPR. Veličković, Petar (2018). Graph Attention Networks. ICLR. Kitaev, Nikita (2020). Reformer: The Efficient

    Attention (machine learning)

    Attention (machine learning)

    Attention_(machine_learning)

  • P versus NP problem
  • Unsolved problem in computer science

    about Turing machines as they relate to the definition of NP. However, after this problem was proved to be NP-complete, proof by reduction provided a simpler

    P versus NP problem

    P_versus_NP_problem

  • Feature (machine learning)
  • Measurable property or characteristic

    tasks. Features are usually numeric, but other types such as strings and graphs are used in syntactic pattern recognition, after some pre-processing step

    Feature (machine learning)

    Feature_(machine_learning)

  • Multimodal representation learning
  • edges. Other graph-based methods include Probabilistic Graphical Models (PGMs) such as deep belief networks (DBN) and deep Boltzmann machines (DBM). These

    Multimodal representation learning

    Multimodal_representation_learning

  • Feedback arc set
  • Edges that hit all cycles in a graph

    In graph theory and graph algorithms, a feedback arc set or feedback edge set in a directed graph is a subset of the edges of the graph that contains at

    Feedback arc set

    Feedback arc set

    Feedback_arc_set

  • Vector database
  • Type of database that uses vectors to represent other data

    analyzing data with many aspects ("dimensions") Graph database – Database using graph structures for queries Machine learning – Subset of artificial intelligence

    Vector database

    Vector_database

  • E-graph
  • Graph data structure

    In computer science, an e-graph is a data structure that stores an equivalence relation over terms of some language. Let Σ {\displaystyle \Sigma } be

    E-graph

    E-graph

  • EXPTIME
  • Algorithmic complexity class

    Turing machine. A decision problem is EXPTIME-complete if it is in EXPTIME and every problem in EXPTIME has a polynomial-time many-one reduction to it

    EXPTIME

    EXPTIME

  • W. T. Tutte
  • British-Canadian codebreaker and mathematician (1917–2002)

    fields of graph theory and matroid theory. Tutte's research in the field of graph theory proved to be of remarkable importance. At a time when graph theory

    W. T. Tutte

    W._T._Tutte

  • APX
  • Complexity class of approximable problems

    independent set in bounded-degree graphs (here, the approximation ratio depends on the maximum degree of the graph, but is constant if the max degree

    APX

    APX

  • Drug overdose
  • Use of an excessive amount of a drug

    Control and Prevention. Click on "Rising Rates" tab for a graph. See data table below the graph. NCHS Data Visualization Gallery—Drug Poisoning Mortality

    Drug overdose

    Drug overdose

    Drug_overdose

  • Graphical model
  • Probabilistic model

    statistics—particularly Bayesian statistics—and machine learning. Generally, probabilistic graphical models use a graph-based representation as the foundation

    Graphical model

    Graphical_model

  • T-distributed stochastic neighbor embedding
  • Technique for dimensionality reduction

    proposed the t-distributed variant. It is a nonlinear dimensionality reduction technique for embedding high-dimensional data for visualization in a low-dimensional

    T-distributed stochastic neighbor embedding

    T-distributed stochastic neighbor embedding

    T-distributed_stochastic_neighbor_embedding

  • Closure problem
  • Computational problem in graph theory

    minimum-weight closure in a vertex-weighted directed graph. It may be solved in polynomial time using a reduction to the maximum flow problem. It may be used to

    Closure problem

    Closure_problem

  • Many-one reduction
  • Type of Turing reduction

    and computational complexity theory, a many-one reduction (also called mapping reduction) is a reduction that converts instances of one decision problem

    Many-one reduction

    Many-one_reduction

  • Topological deep learning
  • Research field in deep learning

    Marc; Kwitt, Roland (2020-11-21). "Graph Filtration Learning". Proceedings of the 37th International Conference on Machine Learning. PMLR: 4314–4323. arXiv:1905

    Topological deep learning

    Topological_deep_learning

  • Tsetlin machine
  • Artificial intelligence algorithm

    Tsetlin machine composites: plug-and-play collaboration between specialized Tsetlin machines Contracting Tsetlin machine with absorbing automata Graph Tsetlin

    Tsetlin machine

    Tsetlin machine

    Tsetlin_machine

  • Reduction strategy
  • Relation specifying a rewrite for each object, compatible with a reduction relation

    Sorbonne Paris Cité. p. 62. Partain, William D. (December 1989). Graph Reduction Without Pointers (PDF) (PhD). University of North Carolina at Chapel

    Reduction strategy

    Reduction_strategy

  • Support vector machine
  • Set of methods for supervised statistical learning

    the most votes determines the instance classification. Directed acyclic graph SVM (DAGSVM) Error-correcting output codes Crammer and Singer proposed a

    Support vector machine

    Support_vector_machine

  • Kernel method
  • Class of algorithms for pattern analysis

    data, graphs, text, images, as well as vectors. Algorithms capable of operating with kernels include the kernel perceptron, support-vector machines (SVM)

    Kernel method

    Kernel_method

  • Canonical form
  • Standard representation of a mathematical object

    normal form. In graph theory, a branch of mathematics, graph canonization is the problem of finding a canonical form of a given graph G. A canonical form

    Canonical form

    Canonical form

    Canonical_form

  • Adversarial machine learning
  • Research field that lies at the intersection of machine learning and computer security

    Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. Machine learning techniques

    Adversarial machine learning

    Adversarial_machine_learning

  • Citation graph
  • Directed graph describing citations in documents

    A citation graph (or citation network), in information science and bibliometrics, is a directed graph that describes the citations within a collection

    Citation graph

    Citation graph

    Citation_graph

  • Cycle double cover
  • Cycles in a graph that cover each edge twice

    every bridgeless graph have a multiset of cycles covering every edge exactly twice? More unsolved problems in mathematics In graph-theoretic mathematics

    Cycle double cover

    Cycle double cover

    Cycle_double_cover

  • Shortest path problem
  • Computational problem of graph theory

    In graph theory, the shortest path problem is the problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights

    Shortest path problem

    Shortest path problem

    Shortest_path_problem

  • Bias–variance tradeoff
  • Property of a model

    In statistics and machine learning, the bias–variance tradeoff describes the relationship between a model's complexity, the accuracy of its predictions

    Bias–variance tradeoff

    Bias–variance tradeoff

    Bias–variance_tradeoff

  • European social model
  • Political-economic model common across Europe

    following: Reduction in poverty. Protection against labour market risks. Rewards for labour participation. The graph on the right shows the reduction in inequality

    European social model

    European_social_model

  • List of NP-complete problems
  • tree problem. Feedback vertex set Feedback arc set Graph coloring Graph homomorphism problem Graph partition into subgraphs of specific types (triangles

    List of NP-complete problems

    List_of_NP-complete_problems

  • Active learning (machine learning)
  • Machine learning strategy

    strategies: Learning is accomplished by applying dimensionality reduction to graphs and figures like scatter plots. Then the user is asked to label the

    Active learning (machine learning)

    Active_learning_(machine_learning)

  • Gradient descent
  • Optimization algorithm

    f {\displaystyle f} is assumed to be defined on the plane, and that its graph has a bowl shape. The blue curves are the contour lines, that is, the regions

    Gradient descent

    Gradient descent

    Gradient_descent

  • Fibrations of graphs
  • In mathematics, a fibration of graphs, or graph fibration, is a homomorphism of directed graphs that satisfies a unique lifting property analogous to that

    Fibrations of graphs

    Fibrations_of_graphs

  • László Lovász
  • Hungarian mathematician (born 1948)

    the president of the Hungarian Academy of Sciences from 2014 to 2020. In graph theory, Lovász's notable contributions include the proofs of Kneser's conjecture

    László Lovász

    László Lovász

    László_Lovász

  • Transformer (deep learning)
  • Algorithm for modelling sequential data

    level. seq2seq – Family of machine learning approaches Circuit (neural network) – Interpretable computational sub-graphs within artificial neural networks

    Transformer (deep learning)

    Transformer (deep learning)

    Transformer_(deep_learning)

  • Wave soldering
  • Electronics soldering process

    appliances). There are many types of wave solder machines; however, the basic components and principles of these machines are the same. The basic equipment used

    Wave soldering

    Wave soldering

    Wave_soldering

  • Poverty reduction
  • Measures to reduce poverty permanently

    Poverty reduction, poverty relief, or poverty alleviation is a set of measures, both economic and humanitarian, that are intended to permanently lift

    Poverty reduction

    Poverty reduction

    Poverty_reduction

  • SL (complexity)
  • determining whether there exists a path between two vertices in an undirected graph, otherwise described as the problem of determining whether two vertices

    SL (complexity)

    SL_(complexity)

  • Bottleneck traveling salesman problem
  • Variant of the traveling salesman problem

    Hamiltonian cycle in a graph G with no edge longer than x?", is NP-complete. NP-completeness follows immediately by a reduction from the problem of finding

    Bottleneck traveling salesman problem

    Bottleneck_traveling_salesman_problem

  • Interaction nets
  • Graphical model of computation

    calculus, such as efficient closed reduction and optimal, in Lévy's sense, Lambdascope. Interactions nets are graph-like structures consisting of agents

    Interaction nets

    Interaction_nets

  • Abyei (town)
  • Place in Abyei Area

    Abyei Area through Good Governance and Poverty Reduction" Archived July 24, 2011, at the Wayback Machine Retrieved 24 July 2009. Aafriquejet; 01.19.2011

    Abyei (town)

    Abyei (town)

    Abyei_(town)

  • Abstraction
  • Process of generalization

    they are not abstract in the sense of the objects in graph 1 below. We might look at other graphs, in a progression from cat to mammal to animal, and see

    Abstraction

    Abstraction

  • Graph homomorphism
  • Structure-preserving correspondence between node-link graphs

    In the mathematical field of graph theory, a graph homomorphism is a mapping between two graphs that respects their structure. More concretely, it is a

    Graph homomorphism

    Graph homomorphism

    Graph_homomorphism

  • Interval scheduling
  • Class of problems in computer science

    maximum independent set in an interval graph. A generalization of the problem considers k > 1 {\displaystyle k>1} machines/resources. Here the goal is to find

    Interval scheduling

    Interval_scheduling

  • David Turner (computer scientist)
  • British computer scientist (1946–2023)

    first for functional programming based on lazy evaluation, combinator graph reduction, and polymorphic types: SASL (1972), Kent Recursive Calculator (KRC)

    David Turner (computer scientist)

    David_Turner_(computer_scientist)

  • Parameterized complexity
  • Branch of computational complexity theory

    include deciding if a given graph contains a dominating set of size k. deciding if a given nondeterministic multi-tape Turing machine accepts within k steps

    Parameterized complexity

    Parameterized_complexity

  • Maximal independent set
  • Independent set which is not a subset of any other independent set

    In graph theory, a maximal independent set (MIS) or maximal stable set is an independent set that is not a subset of any other independent set. In other

    Maximal independent set

    Maximal independent set

    Maximal_independent_set

  • Signal processing
  • Field of electrical engineering

    graph. Graph signal processing presents several key points such as sampling signal techniques, recovery techniques and time-varying techiques. Graph signal

    Signal processing

    Signal processing

    Signal_processing

  • P-complete
  • Class in computational complexity theory

    is in P and every problem in P can be reduced to it by an appropriate reduction. The notion of P-complete decision problems is useful in the analysis

    P-complete

    P-complete

  • NetworkX
  • Python library for graphs and networks

    NetworkX is a Python library for studying graphs and networks. NetworkX is free software released under the BSD-new license. NetworkX began development

    NetworkX

    NetworkX

    NetworkX

  • Calculator
  • Device used for calculations

    calculators even have the ability to do computer algebra. Graphing calculators can be used to graph functions defined on the real line, or higher-dimensional

    Calculator

    Calculator

    Calculator

  • List of algorithms
  • algorithm for constructing maximum-cardinality matching on graphs. Coloring algorithm: algorithms for graph (vertex or edge) coloring (subject to constraints,

    List of algorithms

    List_of_algorithms

  • Braess's paradox
  • Paradox related to increasing roadway capacity

    decreases the energy of the graph. If no driver has a best response, the graph is at equilibrium. Since the energy of the graph strictly decreases with each

    Braess's paradox

    Braess's_paradox

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  • Inference
  • n.

    The act or process of inferring by deduction or induction.

  • Adduction
  • n.

    The action by which the parts of the body are drawn towards its axis]; -- opposed to abduction.

  • Abatement
  • n.

    The amount abated; that which is taken away by way of reduction; deduction; decrease; a rebate or discount allowed.

  • Education
  • n.

    The act or process of educating; the result of educating, as determined by the knowledge skill, or discipline of character, acquired; also, the act or process of training by a prescribed or customary course of study or discipline; as, an education for the bar or the pulpit; he has finished his education.

  • Reaction
  • n.

    The mutual or reciprocal action of chemical agents upon each other, or the action upon such chemical agents of some form of energy, as heat, light, or electricity, resulting in a chemical change in one or more of these agents, with the production of new compounds or the manifestation of distinctive characters. See Blowpipe reaction, Flame reaction, under Blowpipe, and Flame.

  • Reductive
  • n.

    A reductive agent.

  • Induction
  • n.

    A process of demonstration in which a general truth is gathered from an examination of particular cases, one of which is known to be true, the examination being so conducted that each case is made to depend on the preceding one; -- called also successive induction.

  • Production
  • n.

    The act or process or producing, bringing forth, or exhibiting to view; as, the production of commodities, of a witness.

  • Reduction
  • v. t.

    The process of making a copy of something, as a figure, design, or draught, on a smaller scale, preserving the proper proportions.

  • Reduction
  • v. t.

    The operation of restoring a dislocated or fractured part to its former place.

  • Deduction
  • n.

    That which is deducted; the part taken away; abatement; as, a deduction from the yearly rent.

  • Seduction
  • n.

    That which seduces, or is adapted to seduce; means of leading astray; as, the seductions of wealth.

  • Reducement
  • n.

    Reduction.

  • Diisatogen
  • n.

    A red crystalline nitrogenous substance or artificial production, which by reduction passes directly to indigo.

  • Reduction
  • n.

    The act of reducing, or state of being reduced; conversion to a given state or condition; diminution; conquest; as, the reduction of a body to powder; the reduction of things to order; the reduction of the expenses of government; the reduction of a rebellious province.

  • Abduction
  • n.

    The wrongful, and usually the forcible, carrying off of a human being; as, the abduction of a child, the abduction of an heiress.

  • Reduction
  • v. t.

    The bringing of a syllogism in one of the so-called imperfect modes into a mode in the first figure.

  • Deduction
  • n.

    Act of deducting or taking away; subtraction; as, the deduction of the subtrahend from the minuend.

  • Reduction
  • v. t.

    The act, process, or result of reducing; as, the reduction of iron from its ores; the reduction of aldehyde from alcohol.