High Algorithm - Algorithm Distribution by Levels of Difficulty
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Pedro Domingos’s High Algorithm describes the families of various algorithms used in the design of artificial intelligence systems.
The proposed article provides arguments for the specialization of algorithms by levels of complexity.
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For algorithms, Domingos offers a chain of five varieties of algorithms, each of which can evaluate a different algorithm at a certain stage of the study. This article assumes that the algorithms logically follow one after the other. To ensure such a sequence, a pair of algorithms (Bayesian and evolutionary) had to be swapped, and also to change the entry point to the family of algorithms. In the proposed model, the chain begins with processing using the Bayes theorem.
I will give the main sections (levels of complexity) that can be explored to improve the interaction of existing algorithms.
Supergroup - sections of the classification of applications:
Inanimate - inanimate nature
Animate - beings including humans
Cosmic - science, including artificial intelligence
Subgroup - AI algorithms, including science
Bayes - definition of casual communications
Evolution - evolutionary algorithms
Analogy - Pattern Recognition
Symbolic - symbolic calculations
Gradient - mathematical optimization
Let's start with a level about which little is currently known - whether the strings fly there, or dark matter.
Chaos - Inanimate - Bayes - Unrecognizable Primary Chaos
The laws of evolution are confirmed in the animal world, however, evolutionary algorithms are applicable to the microworld with the macrocosm. For example, the rotation of one object around another.
Fractal - Inanimate - Evolution - a fractal structure for cognition
Both mass and weightless photons are reduced to energy using Einstein's formula.
Energy - Inanimate - Analogy - energy
Information properties are in many ways ahead of the appearance of a substance. Information includes not only entropy, but also such properties of the Universe as space and time.
Information - Inanimate - Symbolic Information
The static level includes systems with elements. There are a large number of artificial systems, but geology and astronomy are also involved in natural systems.
Static - Inanimate - Gradient - systems
Processes (mental, social, economic) distinguish living nature from inanimate
Dynamic - Animate - Bayes - Processes
Synergistic phenomena in which a person controls the elements of inanimate nature to change the habitat, allow you to organize living space in accordance with the needs.
Market - Animate - Evolution - Market
An important role in the organization of large groups is played by the possibility of combining "according to interests"
Corporation - Animate - Analogy - Corporations
With further complication, the rules are fixed and specialized bodies appear to monitor the implementation of the rules.
Bureaucratic - Animate - Symbolic - bureaucratic apparatus
When approaching the limit of the population there is a need to control activities that support existing environmental systems.
Ecology - Animate - Gradient - ecology
As humankind (or artificial beings) works, it becomes necessary to expand the occupied territory, which now leads to attempts to conquer outer space.
Space - Cosmic - Bayes - outer space
The exchange of ideas for the purpose of expanding knowledge is similar to the mechanism of animal evolution.
Intellect - Cosmic - Evolution - the development of science
As the number of ideas increases, the need for their classification increases.
Class - Cosmic - Analogy - classification of phenomena
After classification, it becomes possible to determine the reactions of members of classes to environmental change.
General - Cosmic - Symbolic - definition of the laws of nature
It is possible to optimize living and non-living nature to favor the development of nature and society.
Optimal - Cosmic - Gradient - determining the optimal structure
Perhaps the beginning of the next round of learning random occurrences.
Development - preparation
Progress - development
Stabilization - stabilization
Conservation - conservation (not used on its own, disguised as a Development of the next level of development)
Matter - material
Abstract - abstract
It is assumed that this set of attributes constitutes a necessary subset for applying known machine learning algorithms. Using the table of levels of complexity allows you to test the hypothesis of supergroups, subgroups, levels of complexity on data posted on the Internet.
References:
habr.com/post/259291 - Tunnel modeling - version 0.9
habr.com/ru/post/316198 - Suggestion for modifying the rules of the game Life
Pedro Domingos’s High Algorithm describes the families of various algorithms used in the design of artificial intelligence systems.
The proposed article provides arguments for the specialization of algorithms by levels of complexity.
')
For algorithms, Domingos offers a chain of five varieties of algorithms, each of which can evaluate a different algorithm at a certain stage of the study. This article assumes that the algorithms logically follow one after the other. To ensure such a sequence, a pair of algorithms (Bayesian and evolutionary) had to be swapped, and also to change the entry point to the family of algorithms. In the proposed model, the chain begins with processing using the Bayes theorem.
I will give the main sections (levels of complexity) that can be explored to improve the interaction of existing algorithms.
Supergroup - sections of the classification of applications:
Inanimate - inanimate nature
Animate - beings including humans
Cosmic - science, including artificial intelligence
Subgroup - AI algorithms, including science
Bayes - definition of casual communications
Evolution - evolutionary algorithms
Analogy - Pattern Recognition
Symbolic - symbolic calculations
Gradient - mathematical optimization
Level - individual difficulty levels
Inanimate nature:
Let's start with a level about which little is currently known - whether the strings fly there, or dark matter.
Chaos - Inanimate - Bayes - Unrecognizable Primary Chaos
The laws of evolution are confirmed in the animal world, however, evolutionary algorithms are applicable to the microworld with the macrocosm. For example, the rotation of one object around another.
Fractal - Inanimate - Evolution - a fractal structure for cognition
Both mass and weightless photons are reduced to energy using Einstein's formula.
Energy - Inanimate - Analogy - energy
Information properties are in many ways ahead of the appearance of a substance. Information includes not only entropy, but also such properties of the Universe as space and time.
Information - Inanimate - Symbolic Information
The static level includes systems with elements. There are a large number of artificial systems, but geology and astronomy are also involved in natural systems.
Static - Inanimate - Gradient - systems
Nature:
Processes (mental, social, economic) distinguish living nature from inanimate
Dynamic - Animate - Bayes - Processes
Synergistic phenomena in which a person controls the elements of inanimate nature to change the habitat, allow you to organize living space in accordance with the needs.
Market - Animate - Evolution - Market
An important role in the organization of large groups is played by the possibility of combining "according to interests"
Corporation - Animate - Analogy - Corporations
With further complication, the rules are fixed and specialized bodies appear to monitor the implementation of the rules.
Bureaucratic - Animate - Symbolic - bureaucratic apparatus
When approaching the limit of the population there is a need to control activities that support existing environmental systems.
Ecology - Animate - Gradient - ecology
superhuman decisions:
As humankind (or artificial beings) works, it becomes necessary to expand the occupied territory, which now leads to attempts to conquer outer space.
Space - Cosmic - Bayes - outer space
The exchange of ideas for the purpose of expanding knowledge is similar to the mechanism of animal evolution.
Intellect - Cosmic - Evolution - the development of science
As the number of ideas increases, the need for their classification increases.
Class - Cosmic - Analogy - classification of phenomena
After classification, it becomes possible to determine the reactions of members of classes to environmental change.
General - Cosmic - Symbolic - definition of the laws of nature
It is possible to optimize living and non-living nature to favor the development of nature and society.
Optimal - Cosmic - Gradient - determining the optimal structure
Perhaps the beginning of the next round of learning random occurrences.
Periods of developmental levels:
Development - preparation
Progress - development
Stabilization - stabilization
Conservation - conservation (not used on its own, disguised as a Development of the next level of development)
Abstraction - levels of abstractness
Matter - material
Abstract - abstract
Conclusion:
It is assumed that this set of attributes constitutes a necessary subset for applying known machine learning algorithms. Using the table of levels of complexity allows you to test the hypothesis of supergroups, subgroups, levels of complexity on data posted on the Internet.
References:
habr.com/post/259291 - Tunnel modeling - version 0.9
habr.com/ru/post/316198 - Suggestion for modifying the rules of the game Life
Source: https://habr.com/ru/post/435670/
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