The Many Facets of Natural Computing Lila Kari

The Many Facets of Natural Computing Lila Kari Dept. of Computer Science University of Western Ontario London, ON, Canada http: //www. csd. uwo. ca/~lila/ lila@csd. uwo. ca 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 Lila Kari, University of Western Ontario

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

CA Example: Rule 30 111 110 101 100 011 010 001 000 0 1 1 0 Lila Kari, University of Western Ontario

Conus Textile pattern 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, …, xn * weights w 1, …, wn * computes f. A(w 1 x 1 + w 2 x 2 + …+ wnxn) • Network Function = vectorial function that, for n input values, associates the outputs of the m pre-selected output neurons Lila Kari, University of Western Ontario

Applications to Human Cognition [T. Schultz, www. psych. mcgill. ca/labs/lnsc] 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 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 Lila Kari, University of Western Ontario

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

Lila Kari, University of Western Ontario

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 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 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 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 Lila Kari, University of Western Ontario

L-Systems Applications • Plant growth [Fuhrer, Wann Jensen, Prusinkiewicz 2004 -05] • Architecture and design [J. Bailey, Archimorph] 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) Lila Kari, University of Western Ontario

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

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

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

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

Computation by DNA Self-Assembly [Mao, La. Bean, Reif, , Seeman, Nature, 2000] 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) Lila Kari, University of Western Ontario

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

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

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

(iii) Nature as Computation Understand nature by viewing natural processes as information processing • Systems Biology • Synthetic Biology • Cellular Computing 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 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 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, 386 bp) of a virus by self-assembly of chemically synthesized short DNA strands Lila Kari, University of Western Ontario

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

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

Biocomputing at Western * UWO Biocomputing Lab http: //www. csd. uwo. ca/~lila/biocomplab. html • DNA COMPUTING, CS 9562 B/4462 B http: //www. csd. uwo. ca/~lila/cs 662. html • UWO Biocomputing Student Award http: //www. csd. uwo. ca/~lila/award. html 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] Lila Kari, University of Western Ontario