Date: Sat, 7 Dec 2013 18:45:35 +0200 (EET) From: Johannes Jost Meixner <xmj@chaot.net> To: FreeBSD-gnats-submit@freebsd.org Subject: ports/184572: [NEW PORT] science/py-pyaixi: Implementation of the MC-AIXI-CTW AI algorithm Message-ID: <2245811489.enqueue@mx12.chaot.net> Resent-Message-ID: <201312071700.rB7H04X9030656@freefall.freebsd.org>
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>Number: 184572 >Category: ports >Synopsis: [NEW PORT] science/py-pyaixi: Implementation of the MC-AIXI-CTW AI algorithm >Confidential: no >Severity: non-critical >Priority: low >Responsible: freebsd-ports-bugs >State: open >Quarter: >Keywords: >Date-Required: >Class: change-request >Submitter-Id: current-users >Arrival-Date: Sat Dec 07 17:00:04 UTC 2013 >Closed-Date: >Last-Modified: >Originator: Johannes Jost Meixner >Release: FreeBSD 11.0-CURRENT amd64 >Organization: Goldener Grund OUe >Environment: System: FreeBSD mx12.chaot.net 11.0-CURRENT FreeBSD 11.0-CURRENT #3: Thu Nov 7 16:08:22 EET >Description: pyaixi is a pure Python implementation of the Monte Carlo-AIXI-Context Tree Weighting (MC-AIXI-CTW) artificial intelligence algorithm. This is an approximation of the AIXI universal artificial intelligence algorithm, which describes a model-based, reinforcement-learning agent capable of general learning. WWW: https://github.com/gkassel/pyaixi Generated with FreeBSD Port Tools 0.99_8 (mode: new) >How-To-Repeat: >Fix: --- .shar begins here --- # This is a shell archive. Save it in a file, remove anything before # this line, and then unpack it by entering "sh file". Note, it may # create directories; files and directories will be owned by you and # have default permissions. # # This archive contains: # # py-pyaixi # py-pyaixi/pkg-descr # py-pyaixi/Makefile # py-pyaixi/distinfo # echo c - py-pyaixi mkdir -p py-pyaixi > /dev/null 2>&1 echo x - py-pyaixi/pkg-descr sed 's/^X//' >py-pyaixi/pkg-descr << 'a764fbf5396cf527a83bec82c25d140d' Xpyaixi is a pure Python implementation of the Monte Carlo-AIXI-Context Tree Weighting X(MC-AIXI-CTW) artificial intelligence algorithm. X XThis is an approximation of the AIXI universal artificial intelligence Xalgorithm, which describes a model-based, reinforcement-learning agent capable Xof general learning. X XWWW: https://github.com/gkassel/pyaixi a764fbf5396cf527a83bec82c25d140d echo x - py-pyaixi/Makefile sed 's/^X//' >py-pyaixi/Makefile << '05f151c3b8e5ab730c594d02c8658d2a' X# Created by: Johannes Meixner <xmj@chaot.net> X# $FreeBSD$ X XPORTNAME= pyaixi XPORTVERSION= 1.0.3 XCATEGORIES= science python XMASTER_SITES= CHEESESHOP XPKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} X XMAINTAINER= xmj@chaot.net XCOMMENT= Implementation of the MC-AIXI-CTW AI algorithm X XLICENSE= CCbySA XLICENSE_NAME= Creative Commons Attribution-ShareAlike 3.0 \ X Unported License XLICENSE_FILE= ${WRKSRC}/LICENSE.txt XLICENSE_PERMS= auto-accept dist-mirror pkg-mirror pkg-sell dist-sell X XUSES= dos2unix XUSE_PYTHON= 2.7 XUSE_PYDISTUTILS= yes XPYDISTUTILS_AUTOPLIST= yes X XPORTDOCS= changelog.txt \ X todo.txt X XPORTEXAMPLES= * X XOPTIONS_DEFINE= DOCS EXAMPLES XOPTIONSFILE?= ${PORT_DBDIR}/py-${PORTNAME}/options XEXAMPLESDIR= ${PREFIX}/share/examples/py-${PORTNAME} XDOCSDIR= ${PREFIX}/share/doc/py-${PORTNAME} X Xpost-install: X ${MKDIR} ${STAGEDIR}${DOCSDIR} X ${INSTALL_DATA} ${PORTDOCS:S|^|${WRKSRC}/doc/|} \ X ${STAGEDIR}${DOCSDIR} X ${MKDIR} ${STAGEDIR}${EXAMPLESDIR} X ${INSTALL_DATA} ${PORTEXAMPLES:S|^|${WRKSRC}/conf/|} \ X ${STAGEDIR}${EXAMPLESDIR} X X.include <bsd.port.mk> 05f151c3b8e5ab730c594d02c8658d2a echo x - py-pyaixi/distinfo sed 's/^X//' >py-pyaixi/distinfo << 'c96bf40ba109252a4c68479c4431f3fc' XSHA256 (pyaixi-1.0.3.tar.gz) = 5d58cd3162740dbf082c16c4a8f377169e6dc4643a1848a4f3a793310ad261db XSIZE (pyaixi-1.0.3.tar.gz) = 48553 c96bf40ba109252a4c68479c4431f3fc exit --- .shar ends here --- >Release-Note: >Audit-Trail: >Unformatted:
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