Mirror | rorriM

My house has many mansions

Ξ October 25th, 2005 | → 0 Comments | ∇ Misc |

My house has many mansions.

I am Dr Franz Von Pauli.

I am convinced we can walk through walls.

Not only me, anyone... Cops... People...

People from Nashville

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Starry Nights | American Museum of Natural History

Ξ October 24th, 2005 | → 0 Comments | ∇ Music |

STARRY NIGHTS SWINGS INTO FALL
WITH LIVE JAZZ AT THE ROSE CENTER
FOR EARTH AND SPACE

Starry Nights continues at the American Museum of Natural History's Rose Center for Earth and Space with sizzling live jazz in one of the most spectacular settings in New York. Visitors to Starry Nights, which is presented the first Friday of every month, can also enjoy mouthwatering tapas and wine and other beverages.

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Bah! Live jazz in one of the world's most advanced planetariums? with beverages??? and snacks?!?!?! who ever heard of something so rediculous!!

*quietly packs suitcase and checks plane ticket prices*

If I'm not back in a month, consider me missing, presumed very mellow.

 

Dot com ruled by US law? || kuro5hin.org

Ξ October 24th, 2005 | → 0 Comments | ∇ Computing |

Once upon a time with a simple article about DNS structuring I caused DJBongHit to rush out and buy smokedot.com.

I like to think that this has saved hapless stoner types the world over from hours of confusion, and paranoia caused by finding that the site wasn't there when they, in their herbally induced mental myopia typed in .com instead of .org.

It is not impossible to imagine that stashes and even lives might not have been saved by this philanthropic happenstance, as I am sure there are more than a few out there would have immediately imagined that this apparent absense meant THE MAN was onto them, flushed their makings down the loo and promptly defenestrated themselves with great cries of "woe is me!" to avoid the hideous tortures and probings that THE MAN is infamous for inflicting upon his victii.

Ok sure, you may say it's just a bunch of druggies; but they too, like the humble muskrat, are part of the ecosystem too.

This, was that very article.

 

 

Exposure

Ξ October 24th, 2005 | → 0 Comments | ∇ Arts, Photography |

 

Michael W. Macy: Social Order in Artificial Worlds

Ξ October 24th, 2005 | → 0 Comments | ∇ Science |

Abstract

How does social order emerge among autonomous but interdependent agents? The expectation of future interaction may explain cooperation based on rational foresight, but the "shadow of the future" offers little leverage on the problem of social order in "everyday life" -- the habits of association that generate unthinking compliance with social norms. Everyday cooperation emerges not from the shadow of the future but from the lessons of the past. Rule-based evolutionary models are a promising way to formalize this process. These models may provide new insights into emergent social order -- not only prudent reciprocity, but also expressive and ritual self-sacrifice for the welfare of close cultural relatives.

 

 

Simple Heuristics That Make Us Smart

Ξ October 24th, 2005 | → 0 Comments | ∇ Misc |

How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? In our book, "Simple Heuristics That Make Us Smart," we invite readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional models of rationality in these fields have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and an eternity in which to make choices. But to understand decisions in the real world, we need a different, more psychologically plausible notion of rationality. This book provides such a view. It is about fast and frugal heuristics-simple rules for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices, judgments, and predictions by employing bounded rationality.

But when and how can such fast and frugal heuristics work? What heuristics are in the mind's "adaptive toolbox," and what building blocks compose them? Can judgments based simply on a single reason be as accurate as those based on many reasons? Could having less knowledge even lead to systematically better predictions than having more knowledge? We explore these questions by developing computational models of heuristics and testing them through theoretical analysis and practical experiments with people. We show how fast and frugal heuristics can yield adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high-school drop-out rates, and profiting from the stock market.

 

 

CFinder has moved to http://angel.elte.hu/cfinder.

Ξ October 24th, 2005 | → 0 Comments | ∇ Misc |

CFinder is a free software for finding overlapping dense groups of nodes in networks, based on the Clique Percolation Method, CPM, of Palla et. al. (2005).

CFinder offers a fast and efficient method for clustering data represented by large graphs, such as genetic or social networks and microarray data.


A cluster -- also called community or module -- in a network is a group of nodes more densely connected to each other than to nodes outside the group. In real networks clusters often overlap.







The communities of the word "bright" in a word association network, the South Florida Free Association norms list, represent the different meanings of this word. Communities are color coded, the overlapping nodes and links between them are emphasized in red, and the volume of a ball (the width of a link) is proportional to the total number of communities it belongs to. Parameter values of the algorithm are k=4 and w*=0.025.

 

 

Dawkins Biomorph Viewer

Ξ October 24th, 2005 | → 0 Comments | ∇ Science |

Biomorph Viewer allows you to intervene directly on the genome. Click one of the genes in the last square and move the mouse, the corresponding genes will be automatically modified. If, during this process, the mouse moves from the box of a gene to another one, the second gene will also be modified. Notice that in gene representation, the circle shows the default basic size.

Like for all programs dealing with artificial life, the use of Biomorph Viewer needs efforts. Take time to test the different forms, use random function to get original starting data (you may reduce the number of junctions after selecting random biomorphs). Play on the dynamic modifications of the genome (try to make the biomorph dance on the music you're listening to, it can be quite funny !) Approaching artificial life may not appear immediately obvious. Take time to explore and understand and you'll dive into a fascinating universe !


&nsbp;

 

Thinking about the liquidity trap

Ξ October 24th, 2005 | → 0 Comments | ∇ Science |

THINKING ABOUT THE LIQUIDITY TRAP

Paul Krugman

December 1999



We live in the Age of the Central Banker - an era in which Greenspan, Duisenberg, and Hayami are household words, in which monetary policy is generally believed to be so effective that it cannot safely be left in the hands of politicians who might use it to their advantage. Through much of the world, quasi-independent central banks are now entrusted with the job of steering economies between the rocks of inflation and the whirlpool of deflation. Their judgement is often questioned, but their power is not.

It is therefore ironic as well as unnerving that precisely at this moment, when we have all become sort-of monetarists, the long-scorned Keynesian challenge to monetary policy - the claim that it is ineffective at recession-fighting, because you can%u2019t push on a string - has reemerged as a real issue. So far only Japan has actually found itself in liquidity-trap conditions, but if it has happened once it can happen again, and if it can happen here it presumably can happen elsewhere. So even if Japan does eventually emerge from its slump, the question of how it became trapped and what to do about it remains a pressing one.

 

 

Self-Organizing Systems FAQ for Usenet newsgroup comp.theory.self-org-sys

Ξ October 24th, 2005 | → 0 Comments | ∇ Misc |

The Science of Self-Organizing Systems

The scientific study of self-organizing systems is relatively new, although questions about how organization arises have of course been raised since ancient times. The forms we identify around us are only a small sub-set of those theoretically possible. So why don't we see more variety ? To answer such a question is the reason why we study self-organization.

Many natural systems show organization (e.g. galaxies, planets, chemical compounds, cells, organisms and societies). Traditional scientific fields attempt to explain these features by referencing the micro properties or laws applicable to their component parts, for example gravitation or chemical bonds. Yet we can also approach the subject in a very different way, looking instead for system properties applicable to all such collections of parts, regardless of size or nature. It is here that modern computers prove essential, allowing us to investigate the dynamic changes that occur over vast numbers of time steps and with a large numbers of initial options.

Studying nature requires timescales appropriate for the natural system, and this restricts our studies to identifiable qualities that are easily reproduced, precluding investigations involving the full range of possibilities that may be encountered. However, mathematics deals easily with generalised and abstract systems and produces theorems applicable to all possible members of a class of systems. By creating mathematical models, and running computer simulations, we are able to quickly explore large numbers of possible starting positions and to analyse the common features that result. Even small systems have almost infinite initial options, so even with the fastest computer currently available, we usually can only sample the possibility space. Yet this is often enough for us to discover interesting properties that can then be tested against real systems, thus generating new theories applicable to complex systems and their spontaneous organization.