Re: Introduction to causal dynamics
On Mon, Sep 07, 2020 at 10:11:53AM +, Ralph Alexander Bariz wrote: > Thats ok, then development will stay on my own gitlab instance and official > mirrors nonetheless are hosted by tuxfamily. > I just released v0.2 and would like to package it and push it to debian > repos. However I have no idea how to do it right. Is there some guide? I have assembled some newcomer information for the "Mentoring of the Month" we are running in Debian Med team: https://wiki.debian.org/DebianMed/MoM#preview Debian Science and Debian Med are sharing a very similar policy so you might be able to replace med-team by science-team and should basically know what to do. Hope this helps. Kind regards Andreas. > The output will be multiple packages: > > - libcausal-cpp.deb > - libcausal-cpp-dev.deb > - libcausal-cpp-examples.deb (examples shall stand alone, since they are nice > to just play with... gol implementation n stuff. probably also splitting them > up once and putting them into packages like causal-gol.deb) > - causalviz-cpp.deb (analyzes causal structure and renders it into graphviz > dot graphs... in v0.2 defunct) > > And in future also: > > - libcausal-d.deb > - libcausal-dev.deb > - libcausal-examples.deb > > BR > Ralph > > ‐‐‐ Original Message ‐‐‐ > On Thursday, September 3, 2020 10:25 PM, Anton Gladky > wrote: > > > I have just added you into the Debian Science Group on salsa. > > > > Usually salsa is used to maintain the packaging stuff, but the upstream is > > hosted mostly > > on github/gitlab and similar. > > > > Best regards > > > > Anton > > > > Am Mi., 2. Sept. 2020 um 10:20 Uhr schrieb Ralph Alexander Bariz > > : > > > >> Hi Anton, > >> > >> Since I'm using Debian(in truth Parrot OS, a Debian Testing based > >> derivative) its just natural, that I want to take care to get it into > >> Debian repositories. Also I want to get it away from my quite insecure own > >> gitlab instance, having it on Debian Salsa Git would be perfect. Also I'd > >> like to pass ownership, or at least get some push from somewhere else > >> making it impossible to (get forced to) re-license it. Who knows where > >> home-office rules of theese times lead to, just want to be sure it stays > >> AGPL. Also for sure I'd like to join the team. > >> > >> BR Ralph > >> > >> ‐‐‐ Original Message ‐‐‐ > >> On Tuesday, September 1, 2020 9:35 PM, Anton Gladky > >> wrote: > >> > >>> Hi Ralph, > >>> > >>> thanks for the introduction. Could you please shortly formulate how the > >>> Debian Science Team can be useful for you? > >>> > >>> Best regards > >>> > >>> Anton > >>> > >>> Am So., 30. Aug. 2020 um 14:13 Uhr schrieb Ralph Alexander Bariz > >>> : > >>> > Hi all, > > My name is Ralph Alexander Bariz. I've written a, I think quite usable, > proof of concept for a runtime which should introduce a new kind of > algorithmic dedicated to the graph oriented modeling and execution of > complex non-linear systems. > Please see > https://gitlab.ralph.or.at/causal-rt/wiki/-/blob/ralph/debconf/debconf.odp > Please see the C++ POC Implementation > https://gitlab.ralph.or.at/causal-rt/causal-cpp > I request to move over the whole project group to salsa > https://gitlab.ralph.or.at/causal-rt > My salsa username is "udet". > > Below I've written, for people interested in the why and probably a way > to some kind of new discrete and, error-resistant discretely, executable > physics, the thesis. I would also like this post to be seen as an > official pre-publication of this thesis. > > Thanks. > > Preface: > I'm system analytics and architect, no mathematician. So this wont > contain a lot of numerical math what probably also is not necessary but > instead the results of a structural analysis of what Germans call > "Wirklichkeit". > > While this journey begun with working out a methodology to model and > execute symmetric interaction simulations on GPU's utilizing definite > integrals I was not convinced it could allow to model and execute the > aimed complex systems observed to be real. > It continued passing by actor model systems which were more what I seek > for but still very data oriented while lacking for a definition of "the > how". > > At that time I came into contact with Werner Heisenberg's and Hans-Peter > Dürr's "last assumption" defining a virtual entity they called "Wirks". > This, for me, was the key to understand what we seem to have missed all > the time. Here a discrepancy between the German and the English language > got very obvious. While a certain understanding of "the how" seems to be > deeply integrated into German language, the English language seems to > completely lack it. This discrepancy gets most obvious when thinking > about the classic
Re: Introduction to causal dynamics
Thats ok, then development will stay on my own gitlab instance and official mirrors nonetheless are hosted by tuxfamily. I just released v0.2 and would like to package it and push it to debian repos. However I have no idea how to do it right. Is there some guide? The output will be multiple packages: - libcausal-cpp.deb - libcausal-cpp-dev.deb - libcausal-cpp-examples.deb (examples shall stand alone, since they are nice to just play with... gol implementation n stuff. probably also splitting them up once and putting them into packages like causal-gol.deb) - causalviz-cpp.deb (analyzes causal structure and renders it into graphviz dot graphs... in v0.2 defunct) And in future also: - libcausal-d.deb - libcausal-dev.deb - libcausal-examples.deb BR Ralph ‐‐‐ Original Message ‐‐‐ On Thursday, September 3, 2020 10:25 PM, Anton Gladky wrote: > I have just added you into the Debian Science Group on salsa. > > Usually salsa is used to maintain the packaging stuff, but the upstream is > hosted mostly > on github/gitlab and similar. > > Best regards > > Anton > > Am Mi., 2. Sept. 2020 um 10:20 Uhr schrieb Ralph Alexander Bariz > : > >> Hi Anton, >> >> Since I'm using Debian(in truth Parrot OS, a Debian Testing based >> derivative) its just natural, that I want to take care to get it into Debian >> repositories. Also I want to get it away from my quite insecure own gitlab >> instance, having it on Debian Salsa Git would be perfect. Also I'd like to >> pass ownership, or at least get some push from somewhere else making it >> impossible to (get forced to) re-license it. Who knows where home-office >> rules of theese times lead to, just want to be sure it stays AGPL. Also for >> sure I'd like to join the team. >> >> BR Ralph >> >> ‐‐‐ Original Message ‐‐‐ >> On Tuesday, September 1, 2020 9:35 PM, Anton Gladky wrote: >> >>> Hi Ralph, >>> >>> thanks for the introduction. Could you please shortly formulate how the >>> Debian Science Team can be useful for you? >>> >>> Best regards >>> >>> Anton >>> >>> Am So., 30. Aug. 2020 um 14:13 Uhr schrieb Ralph Alexander Bariz >>> : >>> Hi all, My name is Ralph Alexander Bariz. I've written a, I think quite usable, proof of concept for a runtime which should introduce a new kind of algorithmic dedicated to the graph oriented modeling and execution of complex non-linear systems. Please see https://gitlab.ralph.or.at/causal-rt/wiki/-/blob/ralph/debconf/debconf.odp Please see the C++ POC Implementation https://gitlab.ralph.or.at/causal-rt/causal-cpp I request to move over the whole project group to salsa https://gitlab.ralph.or.at/causal-rt My salsa username is "udet". Below I've written, for people interested in the why and probably a way to some kind of new discrete and, error-resistant discretely, executable physics, the thesis. I would also like this post to be seen as an official pre-publication of this thesis. Thanks. Preface: I'm system analytics and architect, no mathematician. So this wont contain a lot of numerical math what probably also is not necessary but instead the results of a structural analysis of what Germans call "Wirklichkeit". While this journey begun with working out a methodology to model and execute symmetric interaction simulations on GPU's utilizing definite integrals I was not convinced it could allow to model and execute the aimed complex systems observed to be real. It continued passing by actor model systems which were more what I seek for but still very data oriented while lacking for a definition of "the how". At that time I came into contact with Werner Heisenberg's and Hans-Peter Dürr's "last assumption" defining a virtual entity they called "Wirks". This, for me, was the key to understand what we seem to have missed all the time. Here a discrepancy between the German and the English language got very obvious. While a certain understanding of "the how" seems to be deeply integrated into German language, the English language seems to completely lack it. This discrepancy gets most obvious when thinking about the classic definition of causality in both languages. While the English language defines causality as the implication cause -> effect, while cause and effect are both about the "what", the German definition is "Ursache"(cause) -> "Wirkung" while "Wirkung" is not about the "what" but about the "how". Also one might note, the English "reality" covers the German "Realität" but not the German "Wirklichkeit" while the reality is about the set of all being and the "Wirklichkeit" is the set of all happening. When trying to model this thought of a "Wirks" there came up a few implications which made such a model very attractive not only
Re: Introduction to causal dynamics
On Thu, Sep 03, 2020 at 10:25:00PM +0200, Anton Gladky wrote: > I have just added you into the Debian Science Group on salsa. > > Usually salsa is used to maintain the packaging stuff, but the upstream is > hosted mostly > on github/gitlab and similar. ... but typically we store the code of released tarballs. Using Salsa as main development platform of upstream code is not the intended use of those repositories, thought. Having something that is used packaged as long as it has a free license is probably a good idea. The expectantion that others might join in the development is in most cases not really fulfilled - but there is at least a slight chance if it gets more public. Kind regards Andreas. -- http://fam-tille.de
Re: Introduction to causal dynamics
I have just added you into the Debian Science Group on salsa. Usually salsa is used to maintain the packaging stuff, but the upstream is hosted mostly on github/gitlab and similar. Best regards Anton Am Mi., 2. Sept. 2020 um 10:20 Uhr schrieb Ralph Alexander Bariz < ralph.ba...@pm.me>: > Hi Anton, > > Since I'm using Debian(in truth Parrot OS, a Debian Testing based > derivative) its just natural, that I want to take care to get it into > Debian repositories. Also I want to get it away from my quite insecure own > gitlab instance, having it on Debian Salsa Git would be perfect. Also I'd > like to pass ownership, or at least get some push from somewhere else > making it impossible to (get forced to) re-license it. Who knows where > home-office rules of theese times lead to, just want to be sure it stays > AGPL. Also for sure I'd like to join the team. > > BR Ralph > > > > ‐‐‐ Original Message ‐‐‐ > On Tuesday, September 1, 2020 9:35 PM, Anton Gladky > wrote: > > Hi Ralph, > > thanks for the introduction. Could you please shortly formulate how the > Debian Science Team can be useful for you? > > Best regards > > > Anton > > > Am So., 30. Aug. 2020 um 14:13 Uhr schrieb Ralph Alexander Bariz < > ralph.ba...@pm.me>: > >> Hi all, >> >> My name is Ralph Alexander Bariz. I've written a, I think quite usable, >> proof of concept for a runtime which should introduce a new kind of >> algorithmic dedicated to the graph oriented modeling and execution of >> complex non-linear systems. >> Please see >> https://gitlab.ralph.or.at/causal-rt/wiki/-/blob/ralph/debconf/debconf.odp >> Please see the C++ POC Implementation >> https://gitlab.ralph.or.at/causal-rt/causal-cpp >> I request to move over the whole project group to salsa >> https://gitlab.ralph.or.at/causal-rt >> My salsa username is "udet". >> >> Below I've written, for people interested in the why and probably a way >> to some kind of new discrete and, error-resistant discretely, executable >> physics, the thesis. I would also like this post to be seen as an official >> pre-publication of this thesis. >> >> Thanks. >> >> *Preface*: >> I'm system analytics and architect, no mathematician. So this wont >> contain a lot of numerical math what probably also is not necessary but >> instead the results of a structural analysis of what Germans call >> "Wirklichkeit". >> >> While this journey begun with working out a methodology to model and >> execute symmetric interaction simulations on GPU's utilizing definite >> integrals I was not convinced it could allow to model and execute the aimed >> complex systems observed to be real. >> It continued passing by actor model systems which were more what I seek >> for but still very data oriented while lacking for a definition of "the >> how". >> >> At that time I came into contact with Werner Heisenberg's and Hans-Peter >> Dürr's "last assumption" defining a virtual entity they called "Wirks". >> This, for me, was the key to understand what we seem to have missed all the >> time. Here a discrepancy between the German and the English language got >> very obvious. While a certain understanding of "the how" seems to be deeply >> integrated into German language, the English language seems to completely >> lack it. This discrepancy gets most obvious when thinking about the classic >> definition of causality in both languages. While the English language >> defines causality as the implication cause -> effect, while cause and >> effect are both about the "what", the German definition is "Ursache"(cause) >> -> "Wirkung" while "Wirkung" is not about the "what" but about the "how". >> Also one might note, the English "reality" covers the German "Realität" but >> not the German "Wirklichkeit" while the reality is about the set of all >> being and the "Wirklichkeit" is the set of all happening. >> When trying to model this thought of a "Wirks" there came up a few >> implications which made such a model very attractive not only in context of >> Max Planck's assumption of a discrete energy and spacetime but also seems >> to connect the strings in context of thermodynamics and the simple >> question, why there is entropy but also allows to neatly and exactly define >> a model of time and why density(mass and extent) of a system influences the >> flow of time within this system in relation to another system of another >> density. Also it seems, that such a model allows to understand certain >> effects observed in quantum-mechanics and why space is not a that certain >> thing as we use to treat it as. Causal dynamics has implications to the >> concept of "calculus" and neatly defines the symmetric corner-cases where >> it is useful but clearly points out why in "real" asymmetric/complex and >> not dominated(like domination of suns mass where error can but cut as >> negligible) cases it cannot be applied. >> >> In the following lines I will not handle the concrete "proof of concept" >> implementation for classic computing I have
Re: Introduction to causal dynamics
Hi Ralph, thanks for the introduction. Could you please shortly formulate how the Debian Science Team can be useful for you? Best regards Anton Am So., 30. Aug. 2020 um 14:13 Uhr schrieb Ralph Alexander Bariz < ralph.ba...@pm.me>: > Hi all, > > My name is Ralph Alexander Bariz. I've written a, I think quite usable, > proof of concept for a runtime which should introduce a new kind of > algorithmic dedicated to the graph oriented modeling and execution of > complex non-linear systems. > Please see > https://gitlab.ralph.or.at/causal-rt/wiki/-/blob/ralph/debconf/debconf.odp > Please see the C++ POC Implementation > https://gitlab.ralph.or.at/causal-rt/causal-cpp > I request to move over the whole project group to salsa > https://gitlab.ralph.or.at/causal-rt > My salsa username is "udet". > > Below I've written, for people interested in the why and probably a way to > some kind of new discrete and, error-resistant discretely, executable > physics, the thesis. I would also like this post to be seen as an official > pre-publication of this thesis. > > Thanks. > > *Preface*: > I'm system analytics and architect, no mathematician. So this wont contain > a lot of numerical math what probably also is not necessary but instead the > results of a structural analysis of what Germans call "Wirklichkeit". > > While this journey begun with working out a methodology to model and > execute symmetric interaction simulations on GPU's utilizing definite > integrals I was not convinced it could allow to model and execute the aimed > complex systems observed to be real. > It continued passing by actor model systems which were more what I seek > for but still very data oriented while lacking for a definition of "the > how". > > At that time I came into contact with Werner Heisenberg's and Hans-Peter > Dürr's "last assumption" defining a virtual entity they called "Wirks". > This, for me, was the key to understand what we seem to have missed all the > time. Here a discrepancy between the German and the English language got > very obvious. While a certain understanding of "the how" seems to be deeply > integrated into German language, the English language seems to completely > lack it. This discrepancy gets most obvious when thinking about the classic > definition of causality in both languages. While the English language > defines causality as the implication cause -> effect, while cause and > effect are both about the "what", the German definition is "Ursache"(cause) > -> "Wirkung" while "Wirkung" is not about the "what" but about the "how". > Also one might note, the English "reality" covers the German "Realität" but > not the German "Wirklichkeit" while the reality is about the set of all > being and the "Wirklichkeit" is the set of all happening. > When trying to model this thought of a "Wirks" there came up a few > implications which made such a model very attractive not only in context of > Max Planck's assumption of a discrete energy and spacetime but also seems > to connect the strings in context of thermodynamics and the simple > question, why there is entropy but also allows to neatly and exactly define > a model of time and why density(mass and extent) of a system influences the > flow of time within this system in relation to another system of another > density. Also it seems, that such a model allows to understand certain > effects observed in quantum-mechanics and why space is not a that certain > thing as we use to treat it as. Causal dynamics has implications to the > concept of "calculus" and neatly defines the symmetric corner-cases where > it is useful but clearly points out why in "real" asymmetric/complex and > not dominated(like domination of suns mass where error can but cut as > negligible) cases it cannot be applied. > > In the following lines I will not handle the concrete "proof of concept" > implementation for classic computing I have done but use one of its > example's to support some of previously broached claims. Still it has to be > clear, this POC implementation is NOT complete neither correct. Also please > mind, here I define causal dynamics as the thesis observed and deduced but > not as the thesis making philosophical sense. There is an extended thesis > assuming that all systems are continuous in their nature and its aspects > are discretising on interaction but since there, for me, is no hint > available yet, that this could be the case, but even seemingly one that > this might not be the case(entropy) I will not touch this thought at this > point. > > *Definitions*: > >- A "Processor" is an environment allowing the execution of a causal >systems >- An "Aspect" is a piece of Information in context of a system >- A "Wirks" is the necessity of information to change >- A "Tick" is a pattern allowing a processor to process a certain >"Wirks" within a causal system >- A "Wirkung" is a branch of "Wirks" implying each other >- A "Wirklichkeit" is an integral
Introduction to causal dynamics
Hi all, My name is Ralph Alexander Bariz. I've written a, I think quite usable, proof of concept for a runtime which should introduce a new kind of algorithmic dedicated to the graph oriented modeling and execution of complex non-linear systems. Please see https://gitlab.ralph.or.at/causal-rt/wiki/-/blob/ralph/debconf/debconf.odp Please see the C++ POC Implementation https://gitlab.ralph.or.at/causal-rt/causal-cpp I request to move over the whole project group to salsa https://gitlab.ralph.or.at/causal-rt My salsa username is "udet". Below I've written, for people interested in the why and probably a way to some kind of new discrete and, error-resistant discretely, executable physics, the thesis. I would also like this post to be seen as an official pre-publication of this thesis. Thanks. Preface: I'm system analytics and architect, no mathematician. So this wont contain a lot of numerical math what probably also is not necessary but instead the results of a structural analysis of what Germans call "Wirklichkeit". While this journey begun with working out a methodology to model and execute symmetric interaction simulations on GPU's utilizing definite integrals I was not convinced it could allow to model and execute the aimed complex systems observed to be real. It continued passing by actor model systems which were more what I seek for but still very data oriented while lacking for a definition of "the how". At that time I came into contact with Werner Heisenberg's and Hans-Peter Dürr's "last assumption" defining a virtual entity they called "Wirks". This, for me, was the key to understand what we seem to have missed all the time. Here a discrepancy between the German and the English language got very obvious. While a certain understanding of "the how" seems to be deeply integrated into German language, the English language seems to completely lack it. This discrepancy gets most obvious when thinking about the classic definition of causality in both languages. While the English language defines causality as the implication cause -> effect, while cause and effect are both about the "what", the German definition is "Ursache"(cause) -> "Wirkung" while "Wirkung" is not about the "what" but about the "how". Also one might note, the English "reality" covers the German "Realität" but not the German "Wirklichkeit" while the reality is about the set of all being and the "Wirklichkeit" is the set of all happening. When trying to model this thought of a "Wirks" there came up a few implications which made such a model very attractive not only in context of Max Planck's assumption of a discrete energy and spacetime but also seems to connect the strings in context of thermodynamics and the simple question, why there is entropy but also allows to neatly and exactly define a model of time and why density(mass and extent) of a system influences the flow of time within this system in relation to another system of another density. Also it seems, that such a model allows to understand certain effects observed in quantum-mechanics and why space is not a that certain thing as we use to treat it as. Causal dynamics has implications to the concept of "calculus" and neatly defines the symmetric corner-cases where it is useful but clearly points out why in "real" asymmetric/complex and not dominated(like domination of suns mass where error can but cut as negligible) cases it cannot be applied. In the following lines I will not handle the concrete "proof of concept" implementation for classic computing I have done but use one of its example's to support some of previously broached claims. Still it has to be clear, this POC implementation is NOT complete neither correct. Also please mind, here I define causal dynamics as the thesis observed and deduced but not as the thesis making philosophical sense. There is an extended thesis assuming that all systems are continuous in their nature and its aspects are discretising on interaction but since there, for me, is no hint available yet, that this could be the case, but even seemingly one that this might not be the case(entropy) I will not touch this thought at this point. Definitions: - A "Processor" is an environment allowing the execution of a causal systems - An "Aspect" is a piece of Information in context of a system - A "Wirks" is the necessity of information to change - A "Tick" is a pattern allowing a processor to process a certain "Wirks" within a causal system - A "Wirkung" is a branch of "Wirks" implying each other - A "Wirklichkeit" is an integral set of "Wirkung" influencing each other Axioms: - Principle of "demand": nothing happens without triggering interaction as it is required in sum interaction - Principle of "inertia": nothing happens without a sufficient cause (investment of energy by trigger of interaction) - Principle of "exclusivity": no concurrent involvements of a single "aspect" can happen
