Presentation is loading. Please wait.

Presentation is loading. Please wait.

The Many Facets of Natural Computing Lila Kari Dept. of Computer Science University of Western Ontario London, ON, Canada

Similar presentations


Presentation on theme: "The Many Facets of Natural Computing Lila Kari Dept. of Computer Science University of Western Ontario London, ON, Canada"— Presentation transcript:

1 The Many Facets of Natural Computing Lila Kari Dept. of Computer Science University of Western Ontario London, ON, Canada

2 Lila Kari, University of Western Ontario Natural Computing Investigates models and computational techniques inspired by nature Attempts to understand the world around us in terms of information processing Interdisciplinary field that connects computer sciences with natural sciences

3 Lila Kari, University of Western Ontario Natural Computing (i) Nature as Inspiration (ii) Nature as Implementation Substrate (iii) Nature as Computation

4 Lila Kari, University of Western Ontario (i) Nature as Inspiration Cellular Automata – self-reproduction Neural Computation – the brain Evolutionary Computation – evolution Swarm Intelligence – group behaviour Immunocomputing – immune system Artificial Life – properties of life Membrane Computing – cells and membranes Amorphous Computing - morphogenesis

5 Lila Kari, University of Western Ontario 1.Cellular Automata Cellular automaton = dynamical system consisting of a regular grid of cells Space and time and discrete Each cell can be in a finite number of states Each cell changes its state according to a list of transition rules, based on its current state and the states of its neighbours The grid updates its configuration synchronously

6 Lila Kari, University of Western Ontario CA Example: Rule

7 Lila Kari, University of Western Ontario Conus Textile pattern

8 Lila Kari, University of Western Ontario 2.Neural Computation Artificial Neural Network: a network of interconnected artificial neurons Neuron A : * n real- valued inputs x 1,…, x n * weights w 1,…,w n * computes f A (w 1 x 1 + w 2 x 2 + …+ w n x n ) Network Function = vectorial function that, for n input values, associates the outputs of the m pre-selected output neurons

9 Lila Kari, University of Western Ontario Applications to Human Cognition [T.Schultz,

10 Lila Kari, University of Western Ontario 3.Evolutionary Computation Constant or variable-sized population A fitness criterion according to which individuals are evaluated Genetically inspired operators (mutation or recombination of parents) that produce the next generation from the current one

11 Lila Kari, University of Western Ontario Genetic Algorithms Individuals = fixed-length bit strings Mutation = cut-and-paste of a prefix of a parent with a suffix of another Fitness function is problem-dependent If initial population encodes possible solutions to a given problem, then the system evolves to produce a near-optimal solution to the problem Applications: real-valued parameter optimization

12 Lila Kari, University of Western Ontario Using Genetic Algorithms to Create Evolutionary Art [M.Gold]

13 Lila Kari, University of Western Ontario 4.Swarm Intelligence Swarm: group of mobile biological organisms (bacteria, ants, bees, fish, birds) Each individual communicates with others either directly or indirectly by acting on its environment These interactions contribute to collective problem solving = collective intelligence

14 Lila Kari, University of Western Ontario Particle Swarm Optimization Inspired by flocking behaviour of birds Start with a swarm of particles (each representing a potential solution) Particles move through a multidimensional space and positions are updated based on * previous own velocity * tendency towards personal best * tendency toward neighbourhood best

15 Lila Kari, University of Western Ontario Ant Algorithms Model the foraging behaviour of ants In finding the best path between nest and a source of food, ants rely on indirect communication by laying a pheromone trail on the way back (if food is found) and by following concentration of pheromones (if food is sought)

16 Lila Kari, University of Western Ontario

17 5.Immunocomputing Immune system’s function = protect our bodies against external pathogens Role of immune system: recognize cells and categorize them as self or non-self Innate (non-specific) immune system Adaptive (acquired) immune system

18 Lila Kari, University of Western Ontario Artificial Immune Systems Computational aspects of the immune system: distinguishing self from non-self, feature extraction, learning, immunological memory, self-regulation, fault-tolerance Applications: computer virus detection, anomaly detection in a time-series of data, fault diagnosis, pattern recognition

19 Lila Kari, University of Western Ontario 6.Artificial Life ALife attempts to understand the very essence of what it means to be alive Builds ab initio, within in silico computers, artificial systems that exhibit properties normally associated only with living organisms

20 Lila Kari, University of Western Ontario Lindenmayer Systems Parallel rewriting systems Start with an initial word Apply the rewriting rules in parallel to all letters of the word Used, e.g., for modelling of plant growth and morphogenesis

21 Lila Kari, University of Western Ontario L-Systems Applications Plant growth [Fuhrer, Wann Jensen, Prusinkiewicz ] Architecture and design [J.Bailey, Archimorph]

22 Lila Kari, University of Western Ontario Mechanical Artificial Life Evolving populations of artificial creatures in simulated environments Combining the computational and experimental approaches and using rapid manufacturing technology to fabricate physical evolved robots that were selected for certain abilities (to walk or get a cube)

23 Lila Kari, University of Western Ontario How to insert pdf file

24 Lila Kari, University of Western Ontario 7.Membrane Computing Inspired by the compartmentalized internal structure of cells Membrane System = a nested hierarchical structure of regions delimited by “membranes” Each region contains objects and transformation rules + transfer rules

25 Lila Kari, University of Western Ontario 8.Amorphous Computing Inspired by developmental biology Consist of a multitude of irregularly placed, asynchronous, locally interacting computing elements The identically programmed “computational particles” communicate only with others situated within a small radius Goal: engineer specified coherent computational behaviour from the interaction of large quantities of such unreliable computational particles.

26 Lila Kari, University of Western Ontario Amorphous Computing [Generating patterns: Abelson, Sussman, Knight, Ragpal]

27 Lila Kari, University of Western Ontario (ii) Nature as Implementation Substrate Molecular Computing (DNA Computing) Uses biomolecules, e.g., DNA, RNA Quantum Computing Uses, e.g., ion traps, superconductors, nuclear magnetic resonance

28 Lila Kari, University of Western Ontario (ii-1) Molecular Computing Data can be encoded as biomolecules (DNA, RNA) Arithmetic/logic operations are performed by molecular biology tools The proof-of-principle experiment was Adleman’s bio-algorithm solving a Hamiltonian Path Problem (1994)

29 Lila Kari, University of Western Ontario Molecular (DNA) Computing Single-stranded DNA is a string over the four-letter alphabet, {A, C, G, T}

30 Lila Kari, University of Western Ontario Power of DNA Computing Data: DNA single and double strands Watson–Crick Complementarity: W(C) = G, W(A) = T Bio-operations: cut-and-paste by enzymes, extraction by pattern, copy, read-out R.Freund, L.Kari, G.Paun. DNA computing based on splicing: the existence of universal computers. Theory of Computing Systems, 32 (1999).

31 Lila Kari, University of Western Ontario DNA-Encoded Information DNA strands interact with each other in programmed but also undesirable ways The information has no fixed location The results of a biocomputation are not deterministic, as they depend e.g. on concentration of populations of DNA strands, diffusion reactions, statistical laws

32 Lila Kari, University of Western Ontario DNA-Motivated Concepts θ-periodicity w = u 1 u 2 …u n where u i is in {u, θ(u)} and θ is an antimorphic involution Lyndon-Schutzenberger Generalize Lyndon-Schutzenberger u^n v^m = w^m θ-prefix, θ-infix, θ-compliant codes

33 Lila Kari, University of Western Ontario Our DNA Information Research L. Kari, S. Seki, On pseudoknot-bordered words and their properties, Journal of Computer and System Sciences, (2008) L.Kari, K.Mahalingam, Watson-Crick Conjugate and Commutative Words, Proc. DNA Computing 13, LNCS 4848 (2008) L. Kari, K. Mahalingam, S. Seki, Twin-roots of words and their properties, Theoretical Computer Science (2008) E.Czeizler, L.Kari, S.Seki. On a Special Class of Primitive Words. MFCS (2008) M. Ito, L. Kari, Z. Kincaid, S. Seki, Duplication in DNA sequences. Proc. of Developments in Language Theory (2008 )

34 Lila Kari, University of Western Ontario Computing by Self-Assembly Self-Assembly = The process by which objects autonomously come together to form complex structures Examples  Atoms bind by chemical bonds to form molecules  Molecules may form crystals or macromolecules  Cells interact to form organisms

35 Lila Kari, University of Western Ontario Motivation for Self-Assembly Nanotechnology: miniaturization in medicine, electronics, engineering, material science, manufacturing Top-Down techniques: lithography (inefficient in creating structures with size of molecules or atoms) Bottom-Up techniques: self-assembly

36 Lila Kari, University of Western Ontario Computing by Self-Assembly of Tiles Tile = square with the edges labelled from a finite alphabet of glues Tiles cannot be rotated Two adjacent tiles on the plane stick if they have the same glue at the touching edges

37 Lila Kari, University of Western Ontario Computation by DNA Self-Assembly [ Mao, LaBean, Reif,, Seeman, Nature, 2000]

38 Lila Kari, University of Western Ontario Our Self-Assembly Research L.Adleman, J.Kari, L.Kari, D.Reishus, P.Sosik. The Undecidability of the Infinite Ribbon Problem: Implications for Computing by Self-Assembly (SIAM Journal of Computing, to appear, 2009) This solves an open problem formerly known as the “unlimited infinite snake problem” Undecidability of existence of arbitrarily large supertiles that can self-assemble from a given tile set (starting from an arbitrary “seed”) E.Czeizler, L.Kari, Geometrical tile design for complex neighbourhoods (2008, submitted) L.Kari, B.Masson, Simulating arbitrary neighbourhoods by polyominoes (2008, in preparation)

39 Lila Kari, University of Western Ontario DNA Clonable Octahedron [Shih, Joyce, Nature, 2004]

40 Lila Kari, University of Western Ontario Nanoscale DNA Tetrahedra [Goodman, Turberfield, Science, 2005]

41 Lila Kari, University of Western Ontario DNA Origami [Rothemund, Nature, 2006]

42 Lila Kari, University of Western Ontario (ii-2) Quantum Computing A qubit can hold a “0”, a “1” or a quantum superposition of these Quantum mechanical phenomena such as superposition and entanglement are used to perform operations on qubits Shor’s quantum algorithm for factoring integers (1994)

43 Lila Kari, University of Western Ontario Quantum Crytography “Unbreakable encryption unveiled” (BBC News, Oct 2008) “Perfect secrecy has come a step closer with the launch of the world's first computer network protected by unbreakable quantum encryption.” The network connects six locations across Vienna and in the nearby town of St Poelten, using 200 km of standard commercial fibre optic cables.

44 Lila Kari, University of Western Ontario (iii) Nature as Computation Understand nature by viewing natural processesinformation processing natural processes as information processing Systems Biology Synthetic Biology Cellular Computing

45 Lila Kari, University of Western Ontario (iii-1) Systems Biology Attempt to understand complex interactions in biological systems by taking a systemic approach and focusing on the interaction networks themselves and on the properties that arise because of these interactions * gene regulatory networks * protein-protein interaction networks * transport networks

46 Lila Kari, University of Western Ontario The Genomic Computer [ Istrail, De Leon, Davidson, 2007] Molecular transport replaces wires Causal coordination replaces imposed temporal synchrony Changeable architecture replaces rigid structure Communication channels are formed on an as-needed basis Very large scale Robustness is achieved by rigorous selection

47 Lila Kari, University of Western Ontario (iii-2) Synthetic Biology TIMES best inventions 2008 : #21 The Synthetic Organism [C.Venter et al.] Generate a synthetic genome (5,386bp) of a virus by self-assembly of chemically synthesized short DNA strands

48 Lila Kari, University of Western Ontario (iii-3) Cellular Computing Computation in living cells: ciliated protozoa

49 Lila Kari, University of Western Ontario Ciliates: Gene Rearrangement Photo courtesy of L.F. Landweber

50 Lila Kari, University of Western Ontario Our Cellular Computing Research  L.Landweber, L.Kari. The evolution of cellular computing: nature's solution to a computational problem. Biosystems 52(1999)  L.Kari, L.F.Landweber. Computational power of gene rearrangement. Proc. DNA Computing 5, DIMACS Series, 54(2000)  L.Kari, J.Kari, L.Landweber. Reversible molecular computation in ciliates. In Jewels are Forever, Springer-Verlag (1999)

51 Lila Kari, University of Western Ontario Natural Computing Nature as inspiration: cellular automata, neural networks, evolutionary computation, swarm intelligence, immunocomputing, ALife, membrane computing, amorphous computing Nature as implementation substrate: molecular (DNA) computing*, quantum computing Nature as computation: systems biology, synthetic biology, cellular computing* * Research interests of the UWO Biocomputing Lab

52 Lila Kari, University of Western Ontario Biocomputing at Western * UWO Biocomputing Lab DNA COMPUTING, CS 9562B/4462B UWO Biocomputing Student Award

53 Lila Kari, University of Western Ontario Natural Sciences, Ours to Discover “Biology and computer science – life and computation – are related. I am confident that at their interface great discoveries await those who seek them” [Leonard Adleman, Scientific American, August 1998]


Download ppt "The Many Facets of Natural Computing Lila Kari Dept. of Computer Science University of Western Ontario London, ON, Canada"

Similar presentations


Ads by Google