Friday, 25 August 2017

it's a trap!

It all makes horrible sense now!
To truly understand the Brexit debacle, look to Star Wars

Hugely encouraging word from Brussels, where a fan theory has apparently developed around Britain’s Brexit plan. According to a recent Politico report, some on the EU side believe there is no way the UK could truly be as sensationally unprepared and aimless as it has appeared in the early rounds of negotiations, and that it consequently must all be a clever trap.



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Wednesday, 23 August 2017

paths to unconventional computing

Andrew Adamatzky, Selim Akl, Mark Burgin, Cristian S. Calude, José Félix Costa, Mohammad M. Dehshibi, Yukio-Peggio Gunji, Zoran Konkoli, Bruce MacLennan, Bruno Marchal, Maurice Margenstern, Genaro J. Martínez, Richard Mayne, Kenichi Morita, Andrew Schumann, Yaroslav D. Sergeyev, Georgios Ch. Sirakoulis, Susan Stepney, Karl Svozil, Hector Zenil.
East-West Paths to Unconventional Computing
Progress in Biophysics and Molecular Biology, 2017
doi:10.1016/j.pbiomolbio.2017.08.004

This is possibly the strangest paper I have been involved with; it certainly has the most authors!

The abstract says:
Unconventional computing is about breaking boundaries in thinking, acting and computing. Typical topics of this non-typical field include, but are not limited to physics of computation, non-classical logics, new complexity measures, novel hardware, mechanical, chemical and quantum computing. Unconventional computing encourages a new style of thinking while practical applications are obtained from uncovering and exploiting principles and mechanisms of information processing in and functional properties of, physical, chemical and living systems; in particular, efficient algorithms are developed, (almost) optimal architectures are designed and working prototypes of future computing devices are manufactured. This article includes idiosyncratic accounts of ‘unconventional computing’ scientists reflecting on their personal experiences, what attracted them to the field, their inspirations and discoveries.
Surprisingly, perhaps, one of the keywords is “spirituality”.  Now, I agree that Unconventional computing encourages a new style of thinking, but this would be thinking of computation as a physical rather than a mathematical process (in my opinion), and nothing about “spirituality” (whatever that is).

But it was fun for me to write my bit, and to read my co-authors journeys.  You can find a pre-production version, all 82pp of it, here.



Monday, 21 August 2017

book review: Artificial Chemistries

Wolfgang Banzhaf, Lidia Yamamoto.
Artificial Chemistries.
MIT Press. 2015


[disclaimer: I received a copy from the publisher, in order to write this review for Artificial Life, doi: 10.1162/ARTL_r_00239]

An enormous quantity may be termed “astronomical”, referencing the huge span of time since the Big Bang (~ 1017 seconds), the huge size of the universe (~ 1027 metres), or the huge amount of material in the observable universe (~ 1080 atoms). Yet these quantities pale into insignificance compared to those generated by combinatorics, where numbers are combined using multiplication and exponentiation, leading to an “explosion” in their size. The number of possible proteins of the typical length of eukaryotic proteins is 20400 = ~10520 (although not all of these would have a sensible shape or function); the number of possible memory configurations of a mere 1kB of RAM is 28×2^10 = ~1010^3; the number of books in Borges’ Library of Babel is more than 1010^6 (yet hardly any are interesting books), they can be shelved in ~ (1010^6) ^ 1010^6 ways ways, and even the libraryʼs catalogue is huge; and so on.

Daniel Dennett, in his book Darwin’s Dangerous Idea, uses a clever trick to remind us of the sheer scales involved. He builds up an intuition, or possibly more of a feeling, of such sizes, then dubs these “Vast”, with a capital V. Ever after, the term Vast evokes that sheer scale.

Within the Vastness of all possibilities, only a subset is somehow “interesting”: most is mere noise. This subset may be Vast in its own right, yet Vanishingly Small relative to the Vastness of all possibilities. How to find such Vanishingly Small needles in the Vastness of a combinatoric haystack?
 
One technique might be dubbed “search and construct”. Search for a useful set of atoms, primitives, components, that form the basis of the Vast combinatorial space. Then use rules and processes to define or generate only those constructs with interesting structure and behaviour within that space. For the Library of Babel, the atoms are characters, the Vastness is all possible books of these characters. But what rules delimit the subspace of interesting books, books that are grammatical, readable, and worthwhile? There is chunking to form higher-level components: words. There are syntactic restrictions on the form of sentences, and further semantic restrictions to be meaningful. But to go further, to construct the subset that is literature, say, requires as yet uncodified human creativity. For computer programming, constructing a member of the interesting subset is a slightly easier task. The primitives are the relevant high-level language constructs and their syntactic constraints, the rules include well-formedness constraints and patterns, yet there is still much creativity needed to construct useful programs.

Many researchers turn to the natural world for inspiration. Evolution is one process that explores these interesting possibilities. It can be considered part of a process that searches for genomes, then constructs phenotypes. Interestingness here is viability. A range of artificial evolutionary algorithms take inspiration from these natural processes. In nature, the starting point for evolution is already something quite complex: an organism, even a single-celled organism, is non-trivial, not a random collection of molecules. Can we find a mechanism for generating this initial complexity?

Underlying life is chemistry. Chemistry is combinatorics par excellence. From a small set of atoms, chemical bonding laws produce a Vast set of molecules with structure and behaviour. It has chunking: atoms can form small molecular building blocks, such as DNA bases and amino acids, that are themselves the components in higher level constructions. Good blocks can be searched and selected for by evolution. As we have seen from the protein example above, the larger molecules produced are still a Vanishingly Small subset of the potential Vastness. Not all combinations of atoms can form stable molecules, and not all molecules that can form have a function or structure that can contribute to further construction.

Artificial Chemistry (AChem) takes such ideas from natural chemistry, in order to generate and explore a variety of forms of combinatoric Vastness in silico. If we think of AChems as a generic form of “search and construct” processes, and as rule-based novelty generators, we can see that they can be applied not simply to “chemical” problems, but to a whole range of domains where such processes are needed and used, including computing, dynamical systems, language and music, and modelling in silico and in vitro complex systems.

An AChem provides three components for virtual world explorations. First, there is the material, the virtual atoms and molecules, that provides the Vast combinatorial space of potential structures. Then there are the reaction rules, the analogues of the laws of nature in our virtual world, which define how the material combines and dissociates, and possibly even how the space it occupies is restructured (such as with P-systems). These rules implicitly define a subspace of possible structures in that Vastness. Finally, there is the algorithm, which lays out our explicit experimental setup to explore that implicit subspace, anywhere from exhaustive search to pouring some virtual stuff in a virtual bucket and watching what happens.

Nature provides just the one particular kind of material—real world atoms and molecules—and one set of rules—chemical bonding and reactions that say which molecules are possible, and which are not. The only freedom the scientist has is in the algorithm: the experimental setup that controls which molecules encounter which others, under what environmental conditions. Despite its real-world constraints, chemistry provides all the richness and complexity sufficient for life itself.

The playpen of AChem is even richer, since we also have the freedom to choose different basic material, and different rules. Yet it has the corresponding downside in that we now have to implement the rules, of our virtual world.

This new book forms a comprehensive introduction to many different facets of the discipline of AChem. The plurality in its title, Artificial Chemistries, indicates the diversity of approaches covered. It covers the why, how, and what of the choices of material, rule, and algorithm, and their consequences. For the beginning student, it provides a wide-ranging review of the subject, and its 1000-item bibliography is a marvellous resource in its own right, providing entry into the relevant scientific literature. For the practising AChemist, it provides an invaluable reference material on all topics in the discipline.

Despite its comprehensive nature, this book is no mere “annotated bibliography”: its structure provides a narrative unity for the discipline. Part I comprises four foundational chapters, laying out the philosophy and scope of the subject, illustrated with some simple example AChems. It includes a primer on basic concepts from chemistry, such as chemical reactions, the law of mass action, equilibrium, chemical bonds and catalysis. It also covers differential equation modelling and computational techniques.

Part II comprises four chapters covering the natural world inspiration. It starts with the chemistry of life, that of biochemistry and large organic molecules including proteins, RNA and DNA. The level of detail is useful for showing the underlying complexity and richness of the chemical processes that are frequently abstracted as mere string concatenation. It would probably do students good to review this material again once they have designed their initial AChem, to help them appreciate the simplifications they have made. The next chapter discuss simple cells, including their structure with lipid walls, and their dynamics in terms of metabolism. It includes discussion of autopoeisis, Robert Rosen’s ideas on organisation in living systems, origin of life theories, and more. All this is necessarily brief, as each topic has deservedly book-length treatment elsewhere, and so things can get quite dense in places: the Rosen section in particular will probably be incomprehensible to anyone who has not already encountered the material. But the bibliography will guide the curious reader to further explanations. Next come chapters on evolution and open-ended systems. Open-endedness is the holy grail of AChems: not only can they explore a Vast configuration space, they may be able to grow this very space by opening up new possibilities and dimensions through their own contingent development. These chapters contain a mix of fairly standard material given added value by being filtered through an AChem perspective—for example, evolutionary dynamics is discussed in terms of chemical reactions—and some quite deep and provocative concepts.

Part III comprises three chapters of massive literature review, documenting and categorising AChems into rewriting systems, automata, and bio-inspired. In rewriting systems the reaction rules state how a particular string or other representation is systematically changed into a new form; these include lambda calculi, P-systems, L-systems, and the like. Automata AChems comprise molecules whose atoms are assembly language-level computational instructions: molecular behaviour is given by the execution of these fragments. These include specific systems such as Tierra and Avida, as well as more generic systems such as cellular automata, von Neumann constructors, and all the way up to Turing Machines. The bio-inspired AChems hold more closely to biological mechanisms, such as enzyme reactions, RNA binding, shape-based lock-and-key binding, genetic networks, and swarms. These chapters demonstrate a strength and weakness of AChems: the ability to build yet another arbitrary complex system. Some of these AChems have been examined in detail over a long period of time by research groups; others exist in only a paper or two from a single doctoral student project. These chapters can be used as a reference to find specific AChems, or as a source material for developing new AChems, hopefully as a synthesis and unification of existing ones. Their comprehensive nature can be a problem on occasion: a whole algorithm may be covered in a single spare sentence. Yet the Vast bibliography leads on to more detail.

Part IV comprises four chapters focussing on the global dynamics of general AChems. Whilst parts II and III will be best for students, this part will be of most value to more experienced researchers. First is a chapter on Organisation Theory, written with Pietro Speroni di Fenizio. This looks at conditions for and properties of closed sets of molecules: sets where each molecule is produced by members of the set, and so the reaction network is closed. The following chapter discusses the dynamics of such organisations: effects of reaction rates and probabilities on their construction and maintenance. Next comes a chapter dealing with what for me is the raison d’être of AChems: emergence. It provides a discussion of relevant topics: self-organisation, non-equilibrium thermodynamics, chaos, downward causation, all as they are relevant to AChems. Several deep and important concepts are each outlined in half a page, and the chapter covers a stunning range of topics. The final chapter in this part continues the theme of emergence by discussing constructive dynamical systems: how AChems can produce novelty.

Part V comprises five chapters on applications of AChems to a wide range of domains. Here we get discussion of everything from robotics to unconventional computation, from nuclear physics to economics, from modelling biological systems to synthetic biology.

The book also includes an appendix giving details of the PyCell AChem package, which provides an immediate entry to computational AChems.

This book is really three or more significant books rolled into one, as needed to cover the breadth of the subject. There are interdisciplinary issues here: a practitioner needs to know a lot about a wide range of subjects. As such, it is a remarkable work of scholarship, bringing together a whole host of diverse information, and synthesising it into a coherent and valuable account of the discipline of Artificial Chemistry. I learned a lot from reading it; not just the material that was new to me, but also new ways of looking at known material, and the valuable syntheses of a wide range of concepts. The authors should be commended for their impressive contribution to the field. Any AChemist, ALifer or, more generally, any nature-inspired computer scientist or engineer, will find Artificial Chemistries a valuable addition to their research bookshelf.




For all my book reviews, see my main website.

Saturday, 19 August 2017

The Geometry of Speed Limiting Resources

Benjamin Russell, Susan Stepney.
The Geometry of Speed Limiting Resources in Physical Models of Computation.
International Journal of Foundations of Computer Science 28(4):321-333, 2017.
doi:10.1142/S0129054117500204

This is the latest paper in our series on using geometrical approaches to determining speed limits for quantum operations: it takes time to change a quantum state, which will limit the speed of quantum computers.  The series started with a generalisation of the Zeppelin navigation problem, and continued with a further generalisation allowing us to use the word “brachistochrone” in the title.  The current paper is a further generalisation still, to a wider class of systems.

Abstract:
We study the maximum speed of quantum computation and how it is affected by limitations on physical resources. We show how the resulting concepts generalize to a broader class of physical models of computation within dynamical systems and introduce a specific algebraic structure representing these speed limits. We derive a family of quantum speed limit results in resource-constrained quantum systems with pure states and a finite dimensional state space, by using a geometric method based on right invariant action functionals on SU(N). We show that when the action functional is bi-invariant, the minimum time for implementing any quantum gate using a potentially time-dependent Hamiltonian is equal to the minimum time when using a constant Hamiltonian, thus constant Hamiltonians are time optimal for these constraints. We give an explicit formula for the time in these cases, in terms of the resource constraint. We show how our method produces a rich family of speed limit results, of which the generalized Margolus–Levitin theorem and the Mandelstam–Tamm inequality are special cases. We discuss the broader context of geometric approaches to speed limits in physical computation, including the way geometric approaches to quantum speed limits are a model for physical speed limits to computation arising from a limited resource.


Thursday, 17 August 2017

book review: Narrative Theory and the Cognitive Sciences

David Herman, ed.
Narrative Theory and the Cognitive Sciences.
CSLI. 2003

The problem is this. We understand the world through narrative (allegedly). Complex systems are unnarratable (so it seems). Therefore, we literally cannot understand complex systems. Since most of today’s big problems are complex systems (climate, poverty, disease, what have you), this is a bit of a snag. A small group of us are working on a research programme called Narrating Complexity; this book provides some background reading for me from the narrative cognition side of the coin.

I haven’t read all of the book, only those chapters that seem immediately relevant to the Narrating Complexity programme (plus a fourth one, as the train was slower that I was expecting). But the chapters I have read are very good, and my ranking is based on these; the book is by no means “unfinishable” according to my classification, it is simply “unfinished”.

Abbott discusses why complex emergent systems may be unnarratable. Turner’s idea of blends compressing down to the human scale might give a hint towards a solution to this. Some system, rather than being a “mere heap”, is being conceptualised as an entity, albeit maybe not with an agency that we would recognise. Herman shows why we need to be able to do this. And Jahn provides the beginnings of a proto-computational model of how parts of the story formation may occur.

Mark Turner. Double-scope Stories.
Humans can recall or imagine stories that run counter to the events we are experiencing, and not get confused by this. We can take a story, and blend it with a real event, to provide new meaning. And we can take two distinct stories, possibly with clashing structures, and blend those, to get a new “double-scope” blended story with its own emergent structures, allowing us to generate novel ideas and concepts. We can continue doing this, until stories have many levels of blended complexity. One of the things such blending can do is compress expansive conceptual structures down to human scale, where we can grasp them. Turner dissects several examples, including: a scene from the 17th century French play Phèdre; a concept such as punishment that is derived from a blend; the Old English poem The Dream of the Rood that has many levels of blending; and even a children’s story that has several sequential blends, and may be thought of as teaching the concept of blending.

H. Porter Abbott. Unnarratable Knowledge: The Difficulty of Understanding Evolution by Natural Selection.
We understand the world through explanatory narratives of entities with agency. Parts of the world that do not have suitable structure are unnarratable, and hence are not easily understood. Evolution is one such process. Neither natural selection nor species have agency, nor are narrative entities. Such processes have two levels: the lower level of swarms of interacting individually-narratable individuals, and the higher level of emergent collective systems that are more than the sum of their individual parts, without narratable agency. Non-scientific forms of explanation, that specifically invent entities with the agency to guide or control the higher levels, have much greater narrative power, and so can find readier acceptance among the public. It may be that complex systems are fundamentally unnarratable: “There isn’t a story. It’s more like tending a garden, only you’re growing it with 10,000 other gardeners.”

David Herman.  Stories as a Tool for Thinking.
Narrative can have many cognitive functions. It is a system for structuring patterns of events progressing through time: for structuring processes. It can be used to “chunk” experiences into “frames” of stereotypical experiences, then used to compare this typical against the actual. This helps us to understand the world more, and therefore have to memorise less. It allows us to generate and evaluate what-if scenarios. It allows us to draw coherent system boundaries: to extract and bound a relevant collection of participants, events, and structures from the overall stream of events we experience. By requiring a “beginning” and “middle” and an “ending”, it allows us to draw temporal system boundaries, and provides a resource for closure. It allows us to conceptualise causal relationships. And it provides a means for people to think together.

Manfred Jahn. Awake! Open your eyes! The Cognitive Logic of External and Internal Stories.
This chapter investigates the difference between external stories (a narrated tale) v internal stories (such as a dream or imagining). However, this apparently simple partition becomes fragmented on deeper investigation, as stories go through several stages of external and internal forms as they develop: they are narrated, heard, internalised, modified, re-narrated, and so on. This leads to a new cyclical model of stories, with a computational flavour.




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Tuesday, 15 August 2017

The Natural Science of Computing

Our Viewpoint article “The Natural Science of Computing” has just been published in the Communications of the ACM.  This is a shorter, less technical, updated, and more opinionated version of our 2014 paper “When Does a Physical System Compute?”

The statement
Computer science is no more about computers than astronomy is about telescopes
is often attributed to Dijsktra.  The published version serves our purposes even better:
Computer science is not about machines, in the same way that astronomy is not about telescopes. There is an essential unity of mathematics and computer science.
In our paper, we take the opposite approach, and argue that
computer science is as much about computers as astronomy is about telescopes
In astronomy, every time a new kind of telescope is pointed at the heavens, new discoveries have been made, leading to new theoretical developments.  Astronomy is all about telescopes. And unconventional computing, located in “weird” substrates, is showing how it might be that computer science is all about (physical) computers.  We might even claim that there is an essential unity of physics and computer science.  We conclude:
Just like astronomy, computer science could describe physical systems in abstract language with predictive power, and thereby drive forward the dual interplay of technology and theoretical advancement.  New computers could inform new computational theories, and those theories could then help us understand the physical world around us.  Such a computer science would indeed be a natural science.


Sunday, 13 August 2017

Helsinki graffiti

Street art seen under an overpass on our walk back to the hotel.  Compare and contrast with Granada graffiti.