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Scoop.it!
This was just a brilliant paper, talking about exactly what I found wrong with (yet) current computational models: http://t.co/pxP6MZMa7T 
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Scoop.it!
From
www
Evolutionary information theory is a constructive approach that studies information in the context of evolutionary processes, which are ubiquitous in nature and society. In this paper, we develop foundations of evolutionary information theory, building several measures of evolutionary information and obtaining their properties. These measures are based on mathematical models of evolutionary computations, machines and automata.
Evolutionary Information Theory Information 2013, 4(2), 124-168; http://dx.doi.org/10.3390/info4020124 Via Complexity Digest
Phillip Trotter's insight:
This looks very promising - one for reading list for holidays.
Scoop.it!
Application and development of computational methods and tools for modeling and analyzing complex biological systems.
Phillip Trotter's insight:
AS some one who deeply subscribes to Chris Langton's view that the natural stufy of Computing is to stufy computation as its writ across all of nature, this research at Microsoft is deeply interesting (and echoes compaies liek Autodesk who come from one discipline and are increasingly looking at life sciences through the view of computing: The Biological Computation group is conducting research to uncover fundamental principles of biological computation: what cells compute, how and why. We focus primarily on developing computational techniques that enable multiscale modelling, from molecules to cells to systems. Our work currently focuses on fundamentals of Biological Computation, with applications in Immunology and Development, together with principles of Programming Life, with applications in DNA Computing and Synthetic Biology. Click on the image or title to learn more.
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Scoop.it!
My preferred job title is 'theorist', but that is often too ambiguous in casual and non-academic conversation, so I often settle for 'computer scientist'. Unfortunately, it seems that the overwhelming majority of people equate ...
Phillip Trotter's insight:
Artem Kaznatcheev, a researcher in theoretical computer science - i.e. the ideas that underpin computing - has a wonderful write up of Stephanie Forrest's Stannislaw Ulam lecture at the SFI on using inspiration from Biology to address challenges in Software industry. The Ulam lecture is available in video - but its a few hours long - through seriously worth watching and covers modern developments in genetic programming and other approaches. If you need an abbrieviated write up of the key ideas underpinning the Professor Forrest's lecture - then Artem's write up is an awesomely succinct. Worth reading (and the lectures linked in his article - are worth watching!)
Scoop.it!
From
vimeo
Presented at the MIT Media Lab on April 4, 2013. A peronal preface: http://worrydream.com/MediaForThinkingTheUnthinkable/note.html For more information about…
Phillip Trotter's insight:
Bret Victor talk on media tools for thinking and how representions map to thinking and building associations which help us understand systems. Worth watching.
Scoop.it!
From
arxiv
The increase of existing computational capabilities has made simulation emerge as a third discipline of Science, lying midway between experimental and purely theoretical branches [1, 2]. Simulation enables the evaluation of quantities which otherwise would not be accessible, helps to improve experiments and provides new insights on systems which are analysed [3-6]. Knowing the fundamentals of computation can be very useful for scientists, for it can help them to improve the performance of their theoretical models and simulations. This review includes some technical essentials that can be useful to this end, and it is devised as a complement for researchers whose education is focused on scientific issues and not on technological respects. In this document we attempt to discuss the fundamentals of High Performance Computing (HPC) [7] in a way which is easy to understand without much previous background. We sketch the way standard computers and supercomputers work, as well as discuss distributed computing and discuss essential aspects to take into account when running scientific calculations in computers. Via Frédéric Amblard
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I remember reading this when first published and its a great paper. Any computational model of human cognition needs to integrate both chemical and eletrical mechanisms into a integrated whole. Great scoop and awesome paper.