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  1. That’s setting the expectation level pretty high. Can he really pull it off? That’s setting the expectation level pretty high. Can he really pull it off? Emergence Explained What’s right and what’s wrong about reductionism The Aerospace Corp. Computer Systems Division Computer Science & Technology Subdivision Information Technology Department Russ Abbott California State University, Los Angeles Department of Computer Science

  2. How macroscopic behavior arises from microscopic behavior. Yaneer Bar-Yam http://necsi.org/guide/concepts/emergence.html Emergencethe holy grail of complex system computing Macro from micro. Multiscale phenomena. Emergent entities (properties or substances) ‘arise’ out of more fundamental entities and yet are ‘novel’ or ‘irreducible’ with respect to them. Stanford Encyclopedia of Philosophy http://plato.stanford.edu/entries/properties-emergent/ The ‘scare’ quotes identify problematic areas.

  3. Emergencethe holy grail of complex system computing The father of genetic algorithms. One of the founders of the Santa Fe Institute. It is unlikely that a topic as complicated as emergence will submit meekly to a concise definition, and I have no such definition to offer. John Holland, Emergence: From Chaos to Order

  4. Physicist (& poet) Cosma Shalizihttp://cscs.umich.edu/~crshalizi/reviews/holland-on-emergence/ Someplace … where quantum field theory meets general relativity and atoms and void merge into one another, we may take “the rules of the game” to be given. But the rest of the observable, exploitable order in the universe benzene molecules, PV = nRT, snowflakes, cyclonic storms, kittens, cats, young love, middle-aged remorse, financial euphoria accompanied with acute gullibility, prevaricating candidates for public office, tapeworms, jet-lag, and unfolding cherry blossoms Where do all these regularities come from? Call this emergence if you like. It’s a fine-sounding word, and brings to mind southwestern creation myths in an oddly apt way.

  5. The ultimate reductionist. Steven Weinberg Weinberg does not deny others the right to drink the orange juice of emergent phenomena — the idea that a system with many mutually interacting parts can lead to novel macroscopic behaviour — but he asserts vigorously his right to drink the gin of reductionism. http://physicsweb.org/articles/review/15/4/1/1 review of Facing Up Reductionism may or may not be a good guide for a program of weather forecasting, but it provides the necessary insight that there are no autonomous laws of weather that are logically independent of the principles of physics. [T]he reductionist view emphasizes that the weather behaves the way it does because of the general principles of aerodynamics, radiation flow, and so on (as well as historical accidents like the size and orbit of the earth), but in order to predict the weather tomorrow it may be more useful to think about cold fronts and thunderstorms. “Reductionism Redux,” in Cornwell, J. (ed), Nature's Imagination: The Frontiers of Scientific Vision, Oxford University Press, 1995 Real or just conceptual conveniences? No autonomous forces; but perhaps autonomous laws.

  6. An originator of and outspoken defender of functionalism “Special Sciences; Still Autonomous after All These Years,” Philosophical Perspectives, 1998. Jerrold Fodor Damn near everything we know about the world suggests that unimaginably complicated to-ings and fro-ings of bits and pieces at the extreme micro-level manage somehow to converge on stable macro-level properties. Mountains are made of all sorts of stuff. [Yet] generalizations about mountains-as-such … continue to serve geology in good stead. Autonomous laws of mountains? Well, I admit that I don’t know why. I don’t even know how to think about why. I expect to figure out why there is anything except physics the day before I figure out why there is anything at all. [T]he somehowreally is entirely mysterious. Why is there anything except physics?

  7. Three types of emergence • Static (petty reductionism) • a house, cloth, hardness, e.g., of a diamond, pressure, temperature. • Dynamic (grand reductionism): most agent-based models, market phenomena, (un)intended consequences. • Entity-environment interactions; stigmergic effects. • Strong: new forces of nature, e.g., vitalism: “life” from “lifeless” chemicals. • Magic; non-reductionist; what Weinberg doesn’t like. • Quantum entanglement violates whole/part (petty) reductionism. • Reductionism doesn’t outlaw new fundamental forces, e.g., dark energy. • But don’t do this too often. Tangent

  8. Reductionism vs. strong emergence Force: any influence [that] tends to change [the motion of] an object. http://hyperphysics.phy-astr.gsu.edu/hbase/hframe.html Link structure to time Reductionism:the onlyforces in the universe are the n fundamental forces, for some smalln. Strong emergence:new forces of nature may appear at many levels of emergence. An absolutely stark choice. What are the forces that make things happen?

  9. A resident of a primitive society would be quite surprised to see someone assemble a car from its components and then get in and drive off. Surprise is not the point Tangent

  10. Is emergence (just) epiphenomenal? • Epiphenomenon: a secondary phenomenon that is a by-product of another phenomenon. http://wordnet.princeton.edu/ • “[Species diversification] is an epiphenomenon of the basic components of replicating DNA, mutations, geography, and limiting resources.” http://lifesci.rutgers.edu/~heylab/sconcept/conclusions.html • The elliptical shape of the earth’s orbit is an epiphenomenon of the force of gravity acting on a body in motion. • Imagine the earth as an “agent” that follows the (local) rules of inertia and gravitational attraction. Just one last philosophicalconcept. A very strange idea.

  11. The Game of LifeTry to take it seriously as a (very) simple agent-based model. • Agent-based model. • Universe as CA. • (Later) programming platform. • Built on a rectangular grid. • A totalistic two-dimensional cellular automaton. • An agent (cell) is either alive or dead. (Can’t move.) • Rules [analogous to the basic forces of nature; Fredkin & Zuse, Wolfram,http://www.math.usf.edu/~eclark/ANKOS_zuse_fredkin_thesis.html] • The 8 surrounding agents are an agent’s neighbors. • A live agent with two or three live neighbors stays alive; otherwise it dies. • A dead agent with exactly three live neighbors is (miraculously) (re)born and becomes alive. • Article: http://www.math.com/students/wonders/life/life.html (bad applet?) • Applet: http://www.ibiblio.org/lifepatterns/

  12. All software is stigmergically epiphenomenal over the instruction execution cycle, which is stigmergically epiphenomenal over electron flows. The rules are the only forces! Epiphenomenal gliders • Gliders (waves of births and deaths? epidemics?) are (amazing) epiphenomena of the Game of Life rules—whose only(!) consequences are to switch agents/cells on and off. • Gliders (and other epiphenomena) are causally powerless. • A glider does not change how the rules operate or which cells will be switched on and off. A glider doesn’t “go to an agent and turn it on.” • A Game of Life run will proceed in exactly the same way whether one notices the gliders or not. A very reductionist stance. • Agents don’t “notice” gliders—any more than gliders “notice” agents. • Gliders exemplify dynamic emergence. • Gliders are not generated explicitly. • There is no glider algorithm. • Gliders are not visible in the rules. • Gliders are generated stigmergically.

  13. Game of Life Programming Platform You don't do this with your models. • Amazing as they are, gliders are also trivial. • Once we know how to produce a glider, it’s simple to make them. • Can build a library of Game of Life patterns. and their interaction APIs. Also stigmergic. Very fragile. By suitably arranging these patterns, one can simulate a Turing Machine. Paul Rendell.http://rendell.server.org.uk/gol/tmdetails.htm A second level of emergence. Again, no algorithm; just stigmergy.

  14. It’s the design that matters What does it mean for epiphenomenal gliders and other epiphenomenal patterns to simulate a Turing Machine? To prove that a Game-of-Life simulation of a Turing Machine works, must reason about epiphenomenal interactions among epiphenomenal patterns. Must show that the design: • Simulates a Turing Machine. (Reify the design; treat it as real.) • Can be implemented on a Game-of-Life platform. Reductionism: the patterns don’t really interact! Functionalism: it’s (only!) the design that matters. (Set it free!) Multiple possible implementations. Disengage the model from the implementation. Levels of abstraction? Layered hierarchies? Very useful—but not real.

  15. Let’s pretend. A Game of Life anthropologist • Find a lost tribe of Game of Life runs “in the wild.” • Get a grant to study them. • Figure out the Game of Life rules. • Model even explains gliders as emergents! • Publish results. • But the rules do not explain the functionality of a Turing Machine simulation — • which is logically independent of the rules. Lots of autonomous Turing Machines laws! Recall Weinberg: no autonomous weather laws.

  16. Emergence: non-reductive regularity • A regularity: Game-of-Life run simulating a Turing Machine. • Can explain every step by appeal to the Game-of-Life rules. • The rules are the only forces at work. • Yet those rules don’t explain: • Whatthe system is doing functionally. • Howits design is accomplishing it. • Both • Reductionism: only fundamental forces exist. • Emergence (the-whole-is-more-than-just-the-sum-of-its-parts): constructive/creative functionality. Not reducible to rules. • Emergence is any non-reductive functionality/regularity. • Getting epiphenomena to do real work. Recall Shalizi’s notion of emergence as all the order in the universe beyond quarks/strings, etc.

  17. Functionality for an Environment Two sources of design. Too artificial? Too designer-oriented? (General) evolution’s “blind watchmaker” • Something survives if its design/functionality works in its environment. • Functionality understood on its own level. Intelligent designer/architect • Theoretical considerations for a Turing Machine. • Real considerations about a real environment for an embedded system. (Systems engineering/architecting.) In both cases concerned about interaction with an environment. • The functionality is “outward looking” toward the environment. • The “downward looking” implementation isn’t the point.

  18. http://earthobservatory.nasa.gov/Library/Hurricanes/ A hurricane as a far-from-equilibrium entity • Generates heat internally — by condensation rather than combustion. • “Consumes fuel” — different from Prigogine’s dissipative structures. • Energy produced powers its self-perpetuating processes. • Design: a hurricane has adesign; one can talk about how it works. • Fitness: persists (self-perpetuating) as long as the environment within which it finds itself provides adequate resources given its design. • Moist warm surface air — what it “eats.” • Cool dryer condensation area in upper atmosphere — “waste product removal.” Self-perpetuating far-from-equilibrium processes define regions of reduced entropy: you, me, Theseus’s ship, … What’s real?

  19. Dissipative structures vs. self-perpetuating entities Tangent What is the simplest example of a (proto-)biological system with these qualities?

  20. Why are there regularities at all? • Why do un-designed regularities (functionality fragments) such as gliders occur? • Gliders are not designed. • They have no environment to satisfy. • Why is there number theory, e.g., Fermat’s last theorem? • Why is the earth’s orbit a simple ellipse? • “How can it be that mathematics, being after all a product of human thought independent of experience, is so admirably adapted to the objects of reality?” A. Einstein. • “The Unreasonable Effectiveness of Mathematics in the Natural Sciences,” E. Wigner.Communications in Pure and Applied Mathematics, vol. 13, No. I (February 1960). John Wiley & Sons, http://www.dartmouth.edu/~matc/MathDrama/reading/Wigner.html Tangent

  21. Modeling problems:the difficulty of looking downward Can only model unimaginative enemies. Models of computer security or terrorism will always be incomplete. • Strict reductionism implies that it is impossible to find a non-arbitrary base level for models. • What are we leaving out that might matter? • Use Morse code to transmit messages on encrypted lines. • No good models of biological arms races. • Combatants exploit and/or disrupt or otherwise foil each other’s processes. • Insects vs. plants: bark, bark boring, toxin, anti-toxin, … . • Geckos use the Van der Waals “force” to climb. ABM w/GP epiphenomenal Universe is not segmented into disjoint layers.

  22. Can only model unimaginative enemies. Models of computer security or terrorism will always be incomplete. Modeling problems:the difficulty of looking upward • Don’t know how to build models that can notice emergent processes and characterize their interactions. We don’t know what we aren’t noticing. • We/they can use our commercial airline system to deliver mail/bombs. (Food distribution → Botulism toxin.) • Model gravity as an agent-based system. • Ask system to find equation of earth’s orbit. • Once told what to look for, system can find ellipse. • But it won’t notice the yearly cycle of the seasons — even though it is similarly emergent. Exploit an existing process.

  23. Early member of the Santa Fe Institute. The emergence of complexity Image fetching → hit count, Google map hacks, GPS. Real market for virtual assets. James Burke’s Connections. Designs must be implementable not reducible. Condensed matter physics. Anderson: The ability to reduce everything to simple fundamental laws [does not imply] the ability to start from those laws and reconstruct the universe. “More is Different,” Science, 1972. A non-reductive, creative, contingent, stigmergic, historical process. What designers do for a living. What existing processes can I exploit to accomplish my goals? The universe as bricolage

  24. Contact and paper • Russ.Abbott@GMail.com • Emergence Explained (.pdf): • http://abbott.calstatela.edu/PapersAndTalks/Emergence Explained.pdf • Go to http://abbott.calstatela.edu/ and click Emergence Explained. • Search Google for “Emergence Explained”

  25. Foundations Summary slides

  26. Tangent “Downward causation” • Using epiphenomena it’s easy to compute: • the trajectory of a nail on the rim of a rolling wheel (Sperry). • the force applied by one billiard ball to another. • whether a cell in a Game-of-Life grid will ever be turned on by a glider. • the position of the earth in elliptical orbit around the sun. • All are far more complex to compute in terms of fundamental forces. • There is no fundamental force corresponding to kinetic energy. • The gravitational n-body problem has no closed form. • For the glider it’s the difference between partial and total decidability. • When a Game-of-Life Turing Machine turns on a tape cell (or a software animation turns on a phosphor), it is not turning on a grid cell. It is turning on a tape cell that is implemented as a grid cell. Although it may seem like downward causation, it isn’t. The Game-of-Life rules control everything!

  27. Thermodynamic computation:nihil ex nihilo • In Computer Science we assume that one can specify a Turing Machine, a Finite State Automaton, or a piece of software, and it will do its thing — for free. • In the real world one needs energy to drive processes. • To run real software in the real world requires a real computer.

  28. The most interesting entities. Categories of emergent entities • In our examples, gliders are epiphenomena. • In the real world, entities, which represent persistent regions of reduced entropy, are still emergent but real. • Have properties that do not apply to their components and that depend on how they are held together.

  29. Computing/Nature as weak emergence Stigmergy: controlling a process by changing its environment.

  30. Summary • Emergence is non-reductive (creative) regularity/functionality. • Designers produce (usually nominal) emergence all the time. • Weak emergence typically involves indirect interaction through an environment: stigmergy. • Designs must be implementable but not reducible. • Higher level entities (regions of reduced entropy ) are real — not epiphenomenal and not just conceptual conveniences. • Interactions are virtual — and are vulnerable at every level. • Strictly reductionist. • It's important that the interactions accomplish what they are supposed to accomplish within the design. But ultimately, they are epiphenomenal. The only real action is at the lowest level. • Leads to two fundamental modeling problems: difficulty in looking upward and downward.