Re: my artificial scientist
On Sat, Sep 6, 2014 at 1:19 AM, Stephen Paul King stephe...@charter.net wrote: Very Nice Telmo! Thanks Stephen! We need to talk! I am working with Marius Muliga and Lou Kauffman and others on a form of 'software computer that might run on top of your networks! See: http://arxiv.org/abs/1312.4333 This sounds quite interesting (and inline with things I have been thinking about). I will read the article and get back to you, maybe in private. Cheers, Telmo. On Friday, September 5, 2014 8:20:20 AM UTC-4, telmo_menezes wrote: Hi all, Since people have been talking about AI, creativity etc., I take the liberty of doing a bit of self-promotion. My paper Symbolic regression of generative network models has finally been published and it's open access. Here's a blog post about it: http://www.telmomenezes.com/2014/09/using-evolutionary- computation-to-explain-network-growth/ and the direct link: http://www.nature.com/srep/2014/140905/srep06284/full/srep06284.html The idea of this work is to use genetic programming to evolve plausible bottom-up network generators. In a sense, the system automatically looks for and validates theories on how a given network was formed. Cheers, Telmo. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
my artificial scientist
Hi all, Since people have been talking about AI, creativity etc., I take the liberty of doing a bit of self-promotion. My paper Symbolic regression of generative network models has finally been published and it's open access. Here's a blog post about it: http://www.telmomenezes.com/2014/09/using-evolutionary-computation-to-explain-network-growth/ and the direct link: http://www.nature.com/srep/2014/140905/srep06284/full/srep06284.html The idea of this work is to use genetic programming to evolve plausible bottom-up network generators. In a sense, the system automatically looks for and validates theories on how a given network was formed. Cheers, Telmo. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
Re: my artificial scientist
Telmo, How can you release this to the public, what with it's potential to spontaneously form itself into an AGI? Just kidding, very cool stuff, and an excellent use of evolutionary algorithms. A nice diverse set of networks! Terren On Fri, Sep 5, 2014 at 8:20 AM, Telmo Menezes te...@telmomenezes.com wrote: Hi all, Since people have been talking about AI, creativity etc., I take the liberty of doing a bit of self-promotion. My paper Symbolic regression of generative network models has finally been published and it's open access. Here's a blog post about it: http://www.telmomenezes.com/2014/09/using-evolutionary-computation-to-explain-network-growth/ and the direct link: http://www.nature.com/srep/2014/140905/srep06284/full/srep06284.html The idea of this work is to use genetic programming to evolve plausible bottom-up network generators. In a sense, the system automatically looks for and validates theories on how a given network was formed. Cheers, Telmo. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
Re: my artificial scientist
Telmo: Really impressed by your work. The generative rules however must have a low descriptive level in terms of lengths of graphs number of connections etc. Am I right? To earn the status of artificial scientist, How these low level terms can be elevated to tell something meaningful about the concrete problem studied? For example what the generator rule found for Facebook tell about Facebook? I mean, to find a low level generative rule is impressive but are there more? 2014-09-05 14:20 GMT+02:00 Telmo Menezes te...@telmomenezes.com: Hi all, Since people have been talking about AI, creativity etc., I take the liberty of doing a bit of self-promotion. My paper Symbolic regression of generative network models has finally been published and it's open access. Here's a blog post about it: http://www.telmomenezes.com/2014/09/using-evolutionary-computation-to-explain-network-growth/ and the direct link: http://www.nature.com/srep/2014/140905/srep06284/full/srep06284.html The idea of this work is to use genetic programming to evolve plausible bottom-up network generators. In a sense, the system automatically looks for and validates theories on how a given network was formed. Cheers, Telmo. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- Alberto. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
Re: my artificial scientist
On Fri, Sep 5, 2014 at 3:50 PM, Terren Suydam terren.suy...@gmail.com wrote: Telmo, How can you release this to the public, what with it's potential to spontaneously form itself into an AGI? Hey, if it's inevitable, I figure the AGI will be more lenient of me. I suspect we still have a bit of a way to go, though... :) Just kidding, very cool stuff, and an excellent use of evolutionary algorithms. A nice diverse set of networks! Thanks Terren! Terren On Fri, Sep 5, 2014 at 8:20 AM, Telmo Menezes te...@telmomenezes.com wrote: Hi all, Since people have been talking about AI, creativity etc., I take the liberty of doing a bit of self-promotion. My paper Symbolic regression of generative network models has finally been published and it's open access. Here's a blog post about it: http://www.telmomenezes.com/2014/09/using-evolutionary-computation-to-explain-network-growth/ and the direct link: http://www.nature.com/srep/2014/140905/srep06284/full/srep06284.html The idea of this work is to use genetic programming to evolve plausible bottom-up network generators. In a sense, the system automatically looks for and validates theories on how a given network was formed. Cheers, Telmo. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
Re: my artificial scientist
On Fri, Sep 5, 2014 at 4:04 PM, Alberto G. Corona agocor...@gmail.com wrote: Telmo: Really impressed by your work. Thanks Alberto! The generative rules however must have a low descriptive level in terms of lengths of graphs number of connections etc. Am I right? Well, the generators simply give you the likelihood of a connection between two given nodes. Iteratively, you can use the generators to produce a graph with n nodes and m connections. So you can use the same generator to produce networks of different sizes, but you do have to predefine the size. To earn the status of artificial scientist, How these low level terms can be elevated to tell something meaningful about the concrete problem studied? Well, it's shut up and calculate type of scientist. Could an AI go all the way and attempt an interpretation? I think so, but unfortunately I don't have the algorithm yet... In the blog post I make an effort to interpret the equations. To try to answer your question, consider the political blogs case. The expression is: w(i, j) = exp(4 - 2d) One possibility that this raises: maybe we can explain bi-partidarism as the simple outcome of social contagion. You ran this generator (for the network size of the real case) and you get two communities with a small interface -- just like the political blog network discussing the elections in 2004. It proves nothing, of course. But it hints at something. For example what the generator rule found for Facebook tell about Facebook? This one seems to match intuition very well. I tells us that people prefer to connect to popular people, and that, at the same time, social cliques from the outside are transferred into facebook. I mean, to find a low level generative rule is impressive but are there more? There are more. The method simply looks for the simplest explanation. It applies Occam's razor, and we found evidence that, in doing that, it tends to converge on similar explanations. It is of course possible that the more complex explanation is the correct one, but here we are faced with the exact same problem that human scientists face. The best we can do is assume that the simpler explanation is more likely. Cheers, Telmo. 2014-09-05 14:20 GMT+02:00 Telmo Menezes te...@telmomenezes.com: Hi all, Since people have been talking about AI, creativity etc., I take the liberty of doing a bit of self-promotion. My paper Symbolic regression of generative network models has finally been published and it's open access. Here's a blog post about it: http://www.telmomenezes.com/2014/09/using-evolutionary-computation-to-explain-network-growth/ and the direct link: http://www.nature.com/srep/2014/140905/srep06284/full/srep06284.html The idea of this work is to use genetic programming to evolve plausible bottom-up network generators. In a sense, the system automatically looks for and validates theories on how a given network was formed. Cheers, Telmo. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- Alberto. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
Re: my artificial scientist
On Fri, Sep 5, 2014 at 10:35 AM, Telmo Menezes te...@telmomenezes.com wrote: In the blog post I make an effort to interpret the equations. To try to answer your question, consider the political blogs case. The expression is: w(i, j) = exp(4 - 2d) One possibility that this raises: maybe we can explain bi-partidarism as the simple outcome of social contagion. You ran this generator (for the network size of the real case) and you get two communities with a small interface -- just like the political blog network discussing the elections in 2004. It proves nothing, of course. But it hints at something. This reminds me of http://www.cs.sjsu.edu/~pearce/modules/lectures/abs/as/ca.htm. Ethnic clustering is modeled by cellular automata. Start with a 2D grid of cells of different colors, and a single rule that if a cell doesn't have at least one neighbor of similar color, it swaps with a random cell. The resulting grid converges on uniform blocks of color. It shows that segregation occurs even with a very weak preference to be with others of like color, where color could be stand in for skin color or any other identifying trait. T -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
Re: my artificial scientist
Very nice piece of work, Telmo. I'm sending it to my daughter. I think some of your ideas may be useful in her research on cell signaling. Brent On 9/5/2014 5:20 AM, Telmo Menezes wrote: Hi all, Since people have been talking about AI, creativity etc., I take the liberty of doing a bit of self-promotion. My paper Symbolic regression of generative network models has finally been published and it's open access. Here's a blog post about it: http://www.telmomenezes.com/2014/09/using-evolutionary-computation-to-explain-network-growth/ and the direct link: http://www.nature.com/srep/2014/140905/srep06284/full/srep06284.html The idea of this work is to use genetic programming to evolve plausible bottom-up network generators. In a sense, the system automatically looks for and validates theories on how a given network was formed. Cheers, Telmo. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com mailto:everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com mailto:everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
Re: my artificial scientist
On Fri, Sep 5, 2014 at 7:02 PM, meekerdb meeke...@verizon.net wrote: Very nice piece of work, Telmo. I'm sending it to my daughter. I think some of your ideas may be useful in her research on cell signaling. Thanks Brent! That sounds like fun, please tell her to not hesitate to contact me if she thinks it might be useful. Telmo. Brent On 9/5/2014 5:20 AM, Telmo Menezes wrote: Hi all, Since people have been talking about AI, creativity etc., I take the liberty of doing a bit of self-promotion. My paper Symbolic regression of generative network models has finally been published and it's open access. Here's a blog post about it: http://www.telmomenezes.com/2014/09/using-evolutionary-computation-to-explain-network-growth/ and the direct link: http://www.nature.com/srep/2014/140905/srep06284/full/srep06284.html The idea of this work is to use genetic programming to evolve plausible bottom-up network generators. In a sense, the system automatically looks for and validates theories on how a given network was formed. Cheers, Telmo. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
Re: my artificial scientist
On Fri, Sep 5, 2014 at 4:50 PM, Terren Suydam terren.suy...@gmail.com wrote: On Fri, Sep 5, 2014 at 10:35 AM, Telmo Menezes te...@telmomenezes.com wrote: In the blog post I make an effort to interpret the equations. To try to answer your question, consider the political blogs case. The expression is: w(i, j) = exp(4 - 2d) One possibility that this raises: maybe we can explain bi-partidarism as the simple outcome of social contagion. You ran this generator (for the network size of the real case) and you get two communities with a small interface -- just like the political blog network discussing the elections in 2004. It proves nothing, of course. But it hints at something. This reminds me of http://www.cs.sjsu.edu/~pearce/modules/lectures/abs/as/ca.htm. Ethnic clustering is modeled by cellular automata. Start with a 2D grid of cells of different colors, and a single rule that if a cell doesn't have at least one neighbor of similar color, it swaps with a random cell. The resulting grid converges on uniform blocks of color. It shows that segregation occurs even with a very weak preference to be with others of like color, where color could be stand in for skin color or any other identifying trait. Yes, it's very reminiscent of Schelling's model, no doubt. Here we have something extra that I think is interesting: we started with a real dataset and reverse-engineered it. We found a segregation model without assuming it at the start. Of course this is all speculative: all we really have is an expression. Its interpretation is debatable. Telmo. T -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
Re: my artificial scientist
Very Nice Telmo! We need to talk! I am working with Marius Muliga and Lou Kauffman and others on a form of 'software computer that might run on top of your networks! See: http://arxiv.org/abs/1312.4333 On Friday, September 5, 2014 8:20:20 AM UTC-4, telmo_menezes wrote: Hi all, Since people have been talking about AI, creativity etc., I take the liberty of doing a bit of self-promotion. My paper Symbolic regression of generative network models has finally been published and it's open access. Here's a blog post about it: http://www.telmomenezes.com/2014/09/using-evolutionary-computation-to-explain-network-growth/ and the direct link: http://www.nature.com/srep/2014/140905/srep06284/full/srep06284.html The idea of this work is to use genetic programming to evolve plausible bottom-up network generators. In a sense, the system automatically looks for and validates theories on how a given network was formed. Cheers, Telmo. -- You received this message because you are subscribed to the Google Groups Everything List group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
