Biologically-Inspired Computing Lecture 4

Biologically-Inspired Computing Lecture 4

Informatics biologically-inspired computing luis rocha 2015 lecture 4 biologically Inspired computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics course outlook luis rocha 2015 Sections I485/H400 Assignments: 35% Students will complete 4/5 assignments based on algorithms presented in class Lab meets in I1 (West) 109 on Lab Wednesdays Lab 0 : January 14th (completed) Introduction to Python (No Assignment) Lab 1 : January 28th Measuring Information (Assignment 1) Due February 11th th biologically Lab 2 : February 11 Inspired L-Systems (Assignment 2) computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics Readings until now luis rocha 2015 Class Book Nunes de Castro, Leandro [2006]. Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications. Chapman & Hall. Chapter 1 – Natural Computing Lecture notes Chapter 1: “What is Life?” Chapter 2: “The logical Mechanisms of Life” posted online @ http://informatics.indiana.edu/rocha/i-bic Papers and other materials Life and Information Gleick, J. [2011]. The Information: A History, a Theory, a Flood. Random House. Chapter 8. Kanehisa, M. [2000]. Post-genome Informatics. Oxford University Press. Chapter 1. Logical mechanisms of life (H400, Optional for I485) Langton, C. [1989]. “Artificial Life” In Artificial Life. C. Langton (Ed.). Addison-Wesley. pp. 1-47. Optional Readings Aleksander, I. [2002]. “Understanding Information Bit by biologically Bit”. In: It must be beautiful : great equations of modern Inspired science. G. Farmelo (Ed.), Granta. computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics information of sequential messages luis rocha 2015 rate of removing uncertainty of each symbol Do, do, do, do, do, do, do, do, do Before we leave Lemme tell y’all a lil’ something Uptown Funk you up, Uptown Funk you up Come on, dance “syntactic” surpriseJump on it But what aboutIf you sexy, than flaunt it If you freaky, than own it function andDon’t brag meaning about it, come show me Come on, dance (semantics)? Jump on it If you sexy, than flaunt it Well, it’s Saturday night and we in the spot biologically Inspired Don’t believe me, just watch computing Uptown Funk you up, Uptown Funk you up (say whaa?) Uptown Funk you up, Uptown Funk you up [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics the logical mechanisms of life luis rocha 2015 life-as-it-could-be Chris Langton Artificial Life can contribute to theoretical biology by locating life- as-we-know-it within the larger picture of life-as-it-could-be life as a property of the organization of matter, rather than a property of the matter which is so organized The way information is processed Whereas biology has largely concerned itself with the material basis of life, Artificial Life is concerned with the formal basis of life. views an organism as a large population of simple machines Synthetic approach or emergent behavior biologically Inspired computing Langton, C. [1989]. “Artificial Life” In: Artificial Life. C. Langton (Ed.). Addison-Wesley. pp. 1-47. [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics scientific approaches of life luis rocha 2015 Analytical Synthetic Reduction to (non- Construction from living) components components Reductionism Holist Life is complicated Life is Organization chemistry Networks of Tied to specific components materiality Universal or Does not allow implementation emergence independent Function, control, Emergence measurement, “bottom-up” approach categorization, information are unnecessary biologically “illusions” Inspired computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics what is non-life-as-it-could be? luis rocha 2015 criteria for deciding good simulations or realizations? Alife must be compared to something What is the formal/logical threshold of complexity? Hard Alife must provide a set of rules to distinguish Alife from artificial matter Weak Alife needs to be able to test design principles of life with simulations Bio-inspired computing needs only to produce good results in engineering problems Comparison to “life-like” behavior is too subjective theories of life methodology requires existing theories of life to be compared against contributes to the meta-methodology of Biology test and improve beyond material constraints, such as the incomplete fossil record or measurement of cellular activity biologically Inspired computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics luis rocha 2015 biologically Inspired computing [email protected] INDIANA http://informatics.indiana.edu/rocha/iNature.com; ANDY POTTS; TURING FAMILY-bic UNIVERSITY Informatics cybernetics luis rocha 2015 post-war science Synthetic approach Engineering-inspired Supremacy of mechanism Postwar culture of problem solving Interdisciplinary teams Cross-disciplinary methodology All can be axiomatized and computed Mculloch&Pitts’ work was major influence “A logical calculus of the ideas immanent in nervous activity”. Bulletin of Mathematical Biophysics 5:115-133 (1943). A Turing machine (any function) could be implemented with a network of simple binary switches (if circularity/feedback is present) Warren S. McCulloch Margaret Mead Claude Shannon biologically Inspired computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic Macy Conferences: 1946-53 UNIVERSITY Informatics Cybernetics was born luis rocha 2015 post-war science: the Josiah Macy Jr. Foundation Meetings The Feedback Mechanisms and Circular Causal Systems in Biology and the Social Sciences March 1946 (10 meetings between 1946 and 1953) Interdisciplinary Since a large class of ordinary phenomena exhibit circular causality, and mathematics is accessible, let’s look at them with a war-time team culture Participants John Von Neumann, Leonard Savage, Norbert Wiener, Arturo Rosenblueth, Walter Pitts, Margaret Mead, Heinz von Foerster, Warren McCulloch, Gregory Bateson, Claude Shannon, Ross Ashby, etc. Key concepts Homeostasis, Circular causality requiring negative feedback (postulated to be very common) Present state becomes input for action at biologically next moment: State-determined systems Inspired The mathematics were finally accessible computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics British Cybernetics luis rocha 2015 Turing as cybernetician The Ratio Club (starting in1949) British cybernetics meetings William Ross Ashby, W. Grey Walter, Alan Turing. etc “computation or the faculty of mind which calculates, plans and reasons” Also following Wiener’s use of “Machina ratiocinatrix” in Cybernetics (1948), following Leibniz’ “calculus ratiocinator” biologically Inspired computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics Shannon’s mouse luis rocha 2015 controlling information to achieve life-like behavior trial and error algorithm information as reduction of uncertainty in the presence of alternatives (combinatorics) lifelike behavior trial and error to learn path from many alternatives adapts to new situations how is learning achieved? Correct choices, information gained from reduced uncertainty, must be stored in memory memory of information as a design principle of intelligence in uncertain environments 75 bit memory stored in (telephone) switching relays Brain as (switching) machine biologically Inspired computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics (complex) systems science luis rocha 2015 a science of organization across disciplines Systemhood properties of nature Robert Rosen Systems depends on a specific adjective: thinghood Systemhood: properties of arrangements of items, independent of the items Similar to “setness” or cardinality George Klir Organization can be studied with the mathematics of relations S = (T, R) S: a System, T: a set of things(thinghood), R: a (or set of) relation(s) (Systemhood) Examples Collections of books or music file are sets But organization of such sets are systems biologically (alphabetically, chronologically, Inspired typologically, etc.) computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics complex networks luis rocha 2015 example of general principle of organization Barabasi-Albert Model: leads to power-law node degree distributions in networks Amaral et al: Most real networks have a cut-off distribution for high degree nodes which can be computationally modeled with vertex aging. biologically Inspired computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics artificial life as (complex) systems science luis rocha 2015 systemhood A system possesses systemhood and thinghood properties Thinghood refers to the specific material that makes up the system Systemhood are the abstracted properties E.g. a clock can be made of different things, but there are implementation-independent properties of “clockness” Systems science deals with the implementation-independent aspects of systems Robert Rosen, George Klir… biologically Inspired computing [email protected] INDIANA http://informatics.indiana.edu/rocha/i-bic UNIVERSITY Informatics

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