turing_machine | A simple turing machine , written in Python | Machine Learning library

by phillikus Python Version: Current License: No License

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kandi X-RAY | turing_machine Summary

turing_machine is a Python library typically used in Artificial Intelligence, Machine Learning, Numpy applications. turing_machine has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

A simple Turing machine, written in Python. Check out for more details.

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turing_machine has a low active ecosystem.

It has 11 star(s) with 3 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

turing_machine has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of turing_machine is current.

Quality

turing_machine has no bugs reported.

Security

turing_machine has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

turing_machine does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

turing_machine releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed turing_machine and discovered the below as its top functions. This is intended to give you an instant insight into turing_machine implemented functionality, and help decide if they suit your requirements.

Processes the state
Log the process after step
Move the head
Write character to the tape
Read the next character from the tape
Get the length of the mesh
Get the tape
Remove trailing sharps
Subtract a word
Adds a word
Decrement a word
Simulate a word

Get all kandi verified functions for this library.

turing_machine Key Features

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turing_machine Examples and Code Snippets

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Community Discussions

Trending Discussions on turing_machine

What is the most efficient way to represent the infinite tape of a Turing machine in Python?

QUESTION

What is the most efficient way to represent the infinite tape of a Turing machine in Python?

Asked 2017-Mar-30 at 07:36

A Turing machine manipulates symbols on an infinite strip of tape according to a table of rules.

In my case entries on the tape can be either 0's and 1's (binary).

The tape starts off 'empty' with an infinity of 0's in both positive and negative directions. This tape gets written on based on the rules that the machine follows, potentially adding 0's or 1's to the unwritten edges.

Since the tape values are binary is there a most efficient way to represent them in memory as the machine writes to the tape, adding new values to the left or right? Obviously I don't need to represent the infinite zeros (unwritten tape), but I do need to expand the data structure as new values are added to the ends of the tape.

A python list could do the trick, shown here inserting a 1 on the left:

...

ANSWER

Answered 2017-Mar-30 at 07:36

Given that the tape is infinite at both ends, you will have to consider the (-inf, -1] range of indices too. The best representation, IMO, would be a pair of lists - one for the non-negative range and the other for the negative range (with indexing reversed). As you move beyond the allocated range of the tape, you will simply have to append to the respective list (which, unlike prepending to a list, is a fast operation).

A draft implementation (using an enhanced version of GrowingList from this answer):

Source https://stackoverflow.com/questions/43110398

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install turing_machine

You can download it from GitHub.
You can use turing_machine like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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