The Computational Beauty of Nature
Computer Explorations of Fractals, Chaos,
Complex Systems, and Adaptation

About the Book
  · title page
  · home*
  · cover artwork
  · jacket text
  · table of contents
  · the author*
  · ordering information
Book Contents
  · three themes
  · part synopses
  · selected excerpts
  · all figures from book
  · quotes from book
  · glossary from book
  · bibliography
  · slide show
Source Code
  · overview &
  · FAQ list*
  · download source code
  · java applets
  · news*
  · reviews & awards
  · errata
  · for educators
  · bibliography (BibTeX format)
  · other links
Glossary - N

[ A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z ]


Nash Equilibrium     In game theory, a pair of strategies for a game such that neither player can improve his outcome by changing his strategy. A Nash equilibrium sometimes takes the form of a saddle structure. Under some cases, when a strategy is at a Nash equilibrium with itself, the strategy resembles an evolutionary stable strategy.

Natural Number     Any of the standard counting numbers; a positive integer.

Natural Selection     The natural filtering process by which individuals with higher fitness are more likely to reproduce than individuals with lower fitness.

Neo-Darwinism     A synthesis of Darwinism with the mechanisms of genetics; the idea that adaptation equals a combination of variation, heredity, and selection. See also evolution, inheritable, and natural selection.

Net Input     The weighted sum of incoming signals into a neuron plus a neuron's threshold value.

Neural Network (NN)     A network of neurons that are connected through synapses or weights. In this book, the term is used almost exclusively to denote an artificial neural network and not the real thing. Each neuron performs a simple calculation that is a function of the activations of the neurons that are connected to it. Through feedback mechanisms and/or the nonlinear output response of neurons, the network as a whole is capable of performing extremely complicated tasks, including universal computation and universal approximation. Three different classes of neural networks are feedforward, feedback, and recurrent neural networks, which differ in the degree and type of connectivity that they possess.

Neuron     A simple computational unit that performs a weighted sum on incoming signals, adds a threshold or bias term to this value to yield a net input, and maps this last value through an activation function to compute its own activation. Some neurons, such as those found in feedback or Hopfield networks, will retain a portion of their previous activation.

Newton's Method     An iterative method for finding 0 values of a function.

Niche     A way for an animal to make a living in an ecosystem.

No Free Lunch (NFL)     A theorem that states that in the worst case, and averaged over an infinite number of search spaces, all search methods perform equally well. More than being a condemnation of any search method, the NFL theorem actually hints that most naturally occurring search spaces are, in fact, not random.

Nonlinear     A function that is not linear. Most things in nature are nonlinear. This means that in a very real way, the whole is at least different from the sum of the parts. See also holism.

Not Recursively Enumerable (not-RE)     An infinite set that cannot be recursively enumerated. Sets of this type that are also not co-recursively enumerable are effectively random.

NP     Nondeterministic polynomial time problems; a class of computational problems that may or may not be solvable in polynomial time but are expressed in such a way that candidate solutions can be tested for correctness in polynomial time. See also time complexity and NP-Complete.

NP-Complete     A problem type in which any instance of any other NP class problem can be translated to in polynomial time. This means that if a fast algorithm exists for an NP-complete problem, then any problem that is in NP can be solved with the same algorithm.

Numerical Solution     A solution to a problem that is calculated through a simulation. For example, solving the Three Body Problem is not possible in the worst case; however, with the differential equations that describe the motions of three bodies in space, one could simulate their movements by simulating each time step. Nevertheless, numerical solutions are usually error-prone due to sensitivity and, therefore, can be used to estimate the future for only relatively short time spans, in the worst case.

[ A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z ]

Copyright © Gary William Flake, 1998-2002. All Rights Reserved. Last modified: 30 Nov 2002