📺 A Universal Theory of Life: Math, Art & Information by Sara Walker

A Universal Theory of Life: Math, Art & Information by Sara Walker from TEDxASU
Dr. Walker introduces the concept of information, then proposes that information may be a necessity for biological complexity in this thought-provoking talk on the origins of life. Sara is a theoretical physicist and astrobiologist, researching the origins and nature of life. She is particularly interested in addressing the question of whether or not “other laws of physics” might govern life, as first posed by Erwin Schrodinger in his famous book What is life?. She is currently an Assistant Professor in the School of Earth and Space Exploration and Beyond Center for Fundamental Concepts in Science at Arizona State University. She is also Fellow of the ASU -Santa Fe Institute Center for Biosocial Complex Systems, Founder of the astrobiology-themed social website SAGANet.org, and is a member of the Board of Directors of Blue Marble Space. She is active in public engagement in science, with recent appearances on “Through the Wormhole” and NPR’s Science Friday.

Admittedly, she only had a few short minutes, but it would have been nice if she’d started out with a precise definition of information. I suspect the majority of her audience didn’t know the definition with which she’s working and it would have helped focus the talk.

Her description of Speigelman’s Monster was relatively interesting and not very often seen in much of the literature that covers these areas.

I wouldn’t rate this very highly as a TED Talk as it wasn’t as condensed and simplistic as most, nor was it as hyper-focused, but then again condensing this area into 11 minutes is far from simple task. I do love that she’s excited enough about the topic that she almost sounds a little out of breath towards the end.

There’s an excellent Eddington quote I’ve mentioned before that would have been apropos to have opened up her presentation that might have brought things into higher relief given her talk title:

Suppose that we were asked to arrange the following in two categories–

distance, mass, electric force, entropy, beauty, melody.

I think there are the strongest grounds for placing entropy alongside beauty and melody and not with the first three.

Sir Arthur Stanley Eddington, OM, FRS (1882-1944), a British astronomer, physicist, and mathematician
in The Nature of the Physical World, 1927

 

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🔖 The hidden simplicity of biology by Paul C W Davies and Sara Imari Walker | Reports on Progress in Physics

The hidden simplicity of biology by Paul C W Davies and Sara Imari Walker (Reports on Progress in Physics)
Life is so remarkable, and so unlike any other physical system, that it is tempting to attribute special factors to it. Physics is founded on the assumption that universal laws and principles underlie all natural phenomena, but is it far from clear that there are 'laws of life' with serious descriptive or predictive power analogous to the laws of physics. Nor is there (yet) a 'theoretical biology' in the same sense as theoretical physics. Part of the obstacle in developing a universal theory of biological organization concerns the daunting complexity of living organisms. However, many attempts have been made to glimpse simplicity lurking within this complexity, and to capture this simplicity mathematically. In this paper we review a promising new line of inquiry to bring coherence and order to the realm of biology by focusing on 'information' as a unifying concept.

Downloadable free copy available on ResearchGate.

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🔖 The “Hard Problem” of Life by Sara Imari Walker & Paul C.W. Davies

The "Hard Problem" of Life by Sara Imari Walker, Paul C.W. Davies (arXiv)
Chalmer's famously identified pinpointing an explanation for our subjective experience as the "hard problem of consciousness". He argued that subjective experience constitutes a "hard problem" in the sense that its explanation will ultimately require new physical laws or principles. Here, we propose a corresponding "hard problem of life" as the problem of how `information' can affect the world. In this essay we motivate both why the problem of information as a causal agent is central to explaining life, and why it is hard - that is, why we suspect that a full resolution of the hard problem of life will, similar to as has been proposed for the hard problem of consciousness, ultimately not be reducible to known physical principles. Comments: To appear in "From Matter to Life: Information and Causality". S.I. Walker, P.C.W. Davies and G.F.R. Ellis (eds). Cambridge University Press
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🔖 The Algorithmic Origins of Life – Sara Walker (SETI Talks)

The Algorithmic Origins of Life by Sara I. Walker (SETI Institute Talks)
The origin of life is arguably one of the greatest unanswered questions in science. A primary challenge is that without a proper definition for life -- a notoriously challenging problem in its own right -- the problem of how life began is not well posed. Here we propose that the transition from non-life to life may correspond to a fundamental shift in causal structure, where information gains direct, and context-dependent, causal efficacy over matter, a transition that may be mapped to a nontrivial distinction in how living systems process information. Dr. Walker will discuss potential measures of such a transition, which may be amenable to laboratory study, and how the proposed mechanism corresponds to the onset of the unique mode of (algorithmic) information processing characteristic of living systems.
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🔖 Origins of Life: A Problem for Physics

Origins of Life: A Problem for Physics by Sara I. Walker (arXiv)
The origins of life stands among the great open scientific questions of our time. While a number of proposals exist for possible starting points in the pathway from non-living to living matter, these have so far not achieved states of complexity that are anywhere near that of even the simplest living systems. A key challenge is identifying the properties of living matter that might distinguish living and non-living physical systems such that we might build new life in the lab. This review is geared towards covering major viewpoints on the origin of life for those new to the origin of life field, with a forward look towards considering what it might take for a physical theory that universally explains the phenomenon of life to arise from the seemingly disconnected array of ideas proposed thus far. The hope is that a theory akin to our other theories in fundamental physics might one day emerge to explain the phenomenon of life, and in turn finally permit solving its origins.
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📖 Read pages 51-68 of Complexity and the Economy by W. Brian Arthur

📖 Read pages 51-68 of Complexity and the Economy by W. Brian Arthur

Complexity and the Economy by W. Brian Arthur

An interesting reference to the origin of life and some related research actually pops up in the discussion!

📖 Read pages 43-51 of Complexity and the Economy by W. Brian Arthur

📖 Read pages 43-51 of Complexity and the Economy by W. Brian Arthur

page 45

literally, as in Keynes’ (1936) phrase, taking into account “what average opinion expects the average opinion to be.”

page 46

…perfect rationality in the market cannot be well defined. Infinitely intelligent agents cannot form expectations in a determinate way.

This type of behavior–coming up with appropriate hypothetical models to act upon, strengthening confidence in those that are validated, and discarding those that are not–is called inductive reasoning.

page 47

We see immediately that the market possesses a psychology. We define this as the collection of market hypotheses, or expectational models or mental beliefs, that are being acted upon at a given time.

page 48
the first(?) mention of a genetic model in the book

Complexity and the Economy by W. Brian Arthur

🔖 Proceedings of the Artificial Life Conference 2016

Proceedings of the Artificial Life Conference 2016 by Carlos Gershenson, Tom Froese, Jesus M. Siqueiros, Wendy Aguilar, Eduardo J. Izquierdo and Hiroki Sayama (The MIT Press)
The ALife conferences are the major meeting of the artificial life research community since 1987. For its 15th edition in 2016, it was held in Latin America for the first time, in the Mayan Riviera, Mexico, from July 4 -8. The special them of the conference: How can the synthetic study of living systems contribute to societies: scientifically, technically, and culturally? The goal of the conference theme is to better understand societies with the purpose of using this understanding for a more efficient management and development of social systems.

Free download available.

Proceedings of the Artificial Life Conference 2016

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🎧 Changing Global Diets: the website | Eat This Podcast

Changing Global Diets: the website by Jeremy Cherfas from Eat This Podcast
A fascinating tool for exploring how, where and when diets evolve. Foodwise, what unites Cameroon, Nigeria and Grenada? How about Cape Verde, Colombia and Peru? As of today, you can visit a website to find out. The site is the brainchild of Colin Khoury and his colleagues, and is intended to make it easier to see the trends hidden within 50 years of annual food data from more than 150 countries. If that rings a bell, it may be because you heard the episode around three years ago, in which Khoury and I talked about the massive paper he and his colleagues had published on the global standard diet. Back then, the researchers found it easy enough to explain the overall global trends that emerged from the data, but more detailed questions – about particular crops, or countries, or food groups – were much more difficult to answer. The answer to that one? An interactive website.

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While this seems a short and simple episode with some engaging conversation, it’s the podcast equivalent of the floating duck–things appear smooth and calm on the surface, but the duck is paddling like the devil underneath the surface. The Changing Global Diet website is truly spectacular and portends to have me losing a day’s worth of work or more over the next few days.

Some of the data compilation here as well as some of the visualizations are reminiscent to me of some of César A. Hidalgo’s work at the MIT Media Lab on economic complexity and even language which I’ve briefly mentioned before or bookmarked.[1][2]

I’d be curious to see what some of the data overlays between and among some of these projects looked like and what connections they might show. I suspect that some of the food diversity questions may play into the economic complexities that countries exhibit as well.

If there were longer term data over the past 10,000+ years to make this a big history and food related thing, that would be phenomenal too, though I suspect that there just isn’t enough data to make a longer time line truly useful.

References

[1]
D. Hartmann, M. R. Guevara, C. Jara-Figueroa, M. Aristarán, and C. A. Hidalgo, “Linking Economic Complexity, Institutions, and Income Inequality,” World Development, vol. 93. Elsevier BV, pp. 75–93, May-2017 [Online]. Available: http://dx.doi.org/10.1016/j.worlddev.2016.12.020
[2]
S. Ronen, B. Gonçalves, K. Z. Hu, A. Vespignani, S. Pinker, and C. A. Hidalgo, “Links that speak: The global language network and its association with global fame,” Proceedings of the National Academy of Sciences, vol. 111, no. 52. Proceedings of the National Academy of Sciences, pp. E5616–E5622, 15-Dec-2014 [Online]. Available: http://dx.doi.org/10.1073/pnas.1410931111
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🔖 Complex Networks & Their Applications V

Complex Networks & Their Applications V: Proceedings of the 5th International Workshop on Complex Networks and their Applications by Hocine Cherifi, Sabrina Gaito, Walter Quattrociocchi, Alessandra Sala (Springer)
This book highlights cutting-edge research in the field of network science, offering scientists, researchers and graduate students a unique opportunity to catch up on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the fifth International Workshop on Complex Networks & their Applications (COMPLEX NETWORKS 2016), which took place in Milan during the last week of November 2016. The carefully selected papers are divided into 11 sections reflecting the diversity and richness of research areas in the field. More specifically, the following topics are covered: Network models; Network measures; Community structure; Network dynamics; Diffusion, epidemics and spreading processes; Resilience and control; Network visualization; Social and political networks; Networks in finance and economics; Biological and ecological networks; and Network analysis. DOI: 10.1007/978-3-319-50901-3; Part of the Studies in Computational Intelligence book series (SCI, volume 693)

Book cover of Complex Networks and Their Applications V

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🔖 From Matter to Life: Information and Causality by Sara Imari Walker, Paul C. W. Davies, George F. R. Ellis

From Matter to Life: Information and Causality by by Sara Imari Walker, Paul C. W. Davies, George F. R. Ellis (Cambridge University Press)
Recent advances suggest that the concept of information might hold the key to unravelling the mystery of life's nature and origin. Fresh insights from a broad and authoritative range of articulate and respected experts focus on the transition from matter to life, and hence reconcile the deep conceptual schism between the way we describe physical and biological systems. A unique cross-disciplinary perspective, drawing on expertise from philosophy, biology, chemistry, physics, and cognitive and social sciences, provides a new way to look at the deepest questions of our existence. This book addresses the role of information in life, and how it can make a difference to what we know about the world. Students, researchers, and all those interested in what life is and how it began will gain insights into the nature of life and its origins that touch on nearly every domain of science. Hardcover: 514 pages; ISBN-10: 1107150531; ISBN-13: 978-1107150539;
From Matter to Life: Information and Causality
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📖 Read pages 30-43 of Complexity and the Economy by W. Brian Arthur

📖 Read pages 30-43 of Complexity and the Economy by W. Brian Arthur

Chapter 2 is a nice piece on the El Farol Problem which is a paradox which “represented a decision problem where expectations (forecasts) that many would attend [the El Farol bar] would lead to few attending, and expectations that few would attend would lead to many attending: expectations would lead to outcomes that would negate these expectations.”

Zhang and Challet generalized this problem into the Minority Game in game theoretic form.

Page 31:

There are two reasons for perfect or deductive rationality to break down under complication. The obvious one is that beyond a certain level of of complexity human logical capacity ceases to cope–human rationality is bounded. The other is that in interactive situations of complication, agents cannot rely upon the other agents they are dealing with to behave under perfect rationality, and so they are forced to guess their behavior. This lands them in a world of subjective beliefs and subjective beliefs about subjective beliefs. Objective, well-defined, shared assumptions then cease to apply. In turn, rational, deductive reasoning (deriving a conclusion by perfect logical processes from well-defined premises) itself cannot apply. The problem becomes ill-defined.

This passage, though in an economics text, seems to be a perfect statement about part of the problem of governing in the United States at the moment. I have a thesis that Donald Trump is a system 1 thinker and is generally incapable of system 2 level thought, thus he has no ability to discern the overall complexity of the situations in which he finds himself (or in which the United States finds itself). As a result, he’s unable to effectively lead. From a complexity and game theoretic standpoint, he feels he’s able to perfectly play and win any game. His problem is that he feels like he’s playing tic-tac-toe, while many see at least a game as complex as checkers. In reality, he’s playing a game far more complex than either chess or go.

The overall problem laid out in this chapter is an interesting one vis-a-vis the issues many restaurant startups face, particularly in large cities. How can they best maximize their attendance not only presently, but in the long term while staying afloat in very crowded market places.

Page 38:

The level at which humans can apply perfect rationality is surprisingly modest. Yet it has not been clear how to deal with imperfect or bounded rationality.

Chapter 3 takes a similar problem as Chapter 2 and ups the complexity of the problem somewhat substantially. While I understand that at the time these problems may have seemed cutting edge and incomprehensible to most, I find myself wondering how they didn’t see it all from the beginning.

Complexity and the Economy by W. Brian Arthur
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🔖 An Introduction to Transfer Entropy: Information Flow in Complex Systems

An Introduction to Transfer Entropy: Information Flow in Complex Systems by Terry Bossomaier, Lionel Barnett, Michael Harré, Joseph T. Lizier (Springer; 1st ed. 2016 edition)
This book considers a relatively new metric in complex systems, transfer entropy, derived from a series of measurements, usually a time series. After a qualitative introduction and a chapter that explains the key ideas from statistics required to understand the text, the authors then present information theory and transfer entropy in depth. A key feature of the approach is the authors' work to show the relationship between information flow and complexity. The later chapters demonstrate information transfer in canonical systems, and applications, for example in neuroscience and in finance. The book will be of value to advanced undergraduate and graduate students and researchers in the areas of computer science, neuroscience, physics, and engineering. ISBN: 978-3-319-43221-2 (Print), 978-3-319-43222-9 (Online)

Want to read; h/t to Joseph Lizier.
Continue reading “🔖 An Introduction to Transfer Entropy: Information Flow in Complex Systems”

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Repost of John Carlos Baez’ Biology as Information Dynamics

Biology as Information Dynamics by John Carlos Baez (Google+)
I'm giving a talk at the Stanford Complexity Group this Thursday afternoon, April 20th. If you're around - like in Silicon Valley - please drop by! It will be in Clark S361 at 4 pm. Here's the idea. Everyone likes to say that biology is all about information. There's something true about this - just think about DNA. But what does this insight actually do for us? To figure it out, we need to do some work. Biology is also about things that can make copies of themselves. So it makes sense to figure out how information theory is connected to the 'replicator equation' — a simple model of population dynamics for self-replicating entities. To see the connection, we need to use relative information: the information of one probability distribution relative to another, also known as the Kullback–Leibler divergence. Then everything pops into sharp focus. It turns out that free energy — energy in forms that can actually be used, not just waste heat — is a special case of relative information Since the decrease of free energy is what drives chemical reactions, biochemistry is founded on relative information. But there's a lot more to it than this! Using relative information we can also see evolution as a learning process, fix the problems with Fisher's fundamental theorem of natural selection, and more. So this what I'll talk about! You can see slides of an old version here: http://math.ucr.edu/home/baez/bio_asu/ but my Stanford talk will be videotaped and it'll eventually be here: https://www.youtube.com/user/StanfordComplexity You can already see lots of cool talks at this location! #biology

Wondering if there’s a way I can manufacture a reason to head to Northern California this week…

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🔖 Linking Economic Complexity, Institutions and Income Inequality

Linking Economic Complexity, Institutions and Income Inequality by Dominik Hartmann, Miguel R. Guevara, Cristian Jara-Figueroa, Manuel Aristarán, César A. Hidalgo (arxiv.org)
A country's mix of products predicts its subsequent pattern of diversification and economic growth. But does this product mix also predict income inequality? Here we combine methods from econometrics, network science, and economic complexity to show that countries exporting complex products (as measured by the Economic Complexity Index) have lower levels of income inequality than countries exporting simpler products. Using multivariate regression analysis, we show that economic complexity is a significant and negative predictor of income inequality and that this relationship is robust to controlling for aggregate measures of income, institutions, export concentration, and human capital. Moreover, we introduce a measure that associates a product to a level of income inequality equal to the average GINI of the countries exporting that product (weighted by the share the product represents in that country's export basket). We use this measure together with the network of related products (or product space) to illustrate how the development of new products is associated with changes in income inequality. These findings show that economic complexity captures information about an economy's level of development that is relevant to the ways an economy generates and distributes its income. Moreover, these findings suggest that a country's productive structure may limit its range of income inequality. Finally, we make our results available through an online resource that allows for its users to visualize the structural transformation of over 150 countries and their associated changes in income inequality between 1963 and 2008.

MIT has a pretty good lay-person’s overview of this article. The final published version is separately available.

 

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