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Transcript of Organisation-Oriented Chemical Programming Peter Dittrich Bio Systems Analysis Group Dept. of...
Organisation-Oriented Chemical Programming
Peter Dittrich
Bio Systems Analysis GroupDept. of Mathematics and Computer Science
Friedrich Schiller University Jena
Friedrich-Schiller-Universität Jena Jena Centre for Bioinformatics
Motivation
How to program IT systems using chemical-like systems?
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 2
Overview
1. Why using chemical-like systems?
2. How to find the right chemical program?
3. Example: Maximal independent set problem.
4. Chemical Organization Theory
5. Organization-oriented chemical programming
6. Evolved vs. manual design
7. Messy Chemistries
8. Outlook: Three Open Problems
26.08.2010 Jena 3Peter Dittrich - FSU & JCB Jena
Artificial chemical computing
Chemistry Helps Computing
Real chemical
computing
[J. S. Astor, C. Adami:., Artificial Life 6(3), 189-218, 2000]
26.08.2010 Jena 4Peter Dittrich - FSU & JCB Jena
Artificial chemical computing
Chemistry Helps Computing
Real chemical
computing
[J. S. Astor, C. Adami:., Artificial Life 6(3), 189-218, 2000]
26.08.2010 Jena 5Peter Dittrich - FSU & JCB Jena
COG (MIT, Brooks et al.)
26.08.2010 Jena 6Peter Dittrich - FSU & JCB Jena
PSI (D. Dörner)
26.08.2010 Jena 7Peter Dittrich - FSU & JCB Jena
PSI (D. Dörner)
26.08.2010 Jena 8Peter Dittrich - FSU & JCB Jena
Growing Artificial NNs
[J. S. Astor, Christophs Adami: A Developmental Model for the Evolution of Artificial Neural Networks., Artificial Life 6(3), 189-218, 2000 http://norgev.alife.org/]
[Astor/Adami]
26.08.2010 Jena 9Peter Dittrich - FSU & JCB Jena
Morpho-Genetic Systems
[Source: Espinosa-Soto, C., P. Padilla-Longoria, E. R. Alvarez-Buylla; The Plant Cell, 16:2923-2939 (2004)]
Arabidopsis wild type and ap3 mutant flower
genetic network(local rules)
26.08.2010 Jena 10Peter Dittrich - FSU & JCB Jena
Amorphous Computing
26.08.2010 Jena 11Peter Dittrich - FSU & JCB Jena
Formation of Artificial Organs
cf:. Uwe Brinkschulte et al.26.08.2010 Jena 12Peter Dittrich - FSU & JCB Jena
Formation of Artificial Organs
cf:. Uwe Brinkschulte et al.26.08.2010 Jena 13Peter Dittrich - FSU & JCB Jena
Organic Middleware OCmu
See T. Ungerer, Univ. Augsburg
26.08.2010 Jena 14Peter Dittrich - FSU & JCB Jena
Characteristics of Applications
• Low-level control in a distributed, dynamic, unpredictable, and unreliable IT system.
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 15
Why chemistry?
Compare with conventional and connectionistic computing.
Peter Dittrich - FSU & JCB Jena 1726.08.2010 Jena
“Invisible Networks”
Peter Dittrich - FSU & JCB Jena 1826.08.2010 Jena
Structure-Function-DualismSelf-Modification / Strange Loop
• Dualism of – structure and function – data and program– Tape and machine
• Self-modification(s. higher-order & generative programming)
• Strange loop
Examples:Pi-calculus
FRAGLETS (Tschudin et al.)
Overview
1. Why using chemical-like systems?
2. How to find the right chemical program?
3. Example: Maximal independent set problem.
4. Chemical Organization Theory
5. Organization-oriented chemical programming
6. Evolved vs. manual design
7. Messy Chemistries
8. Outlook: Three Open Problems
26.08.2010 Jena 19Peter Dittrich - FSU & JCB Jena
Programming Chemical Systems
MICRO(reaction rules)
MACRO(desired behavior)
Abstraction Instantiation
Peter Dittrich - FSU & JCB Jena 2126.08.2010 Jena
Approaches
1. Optimization (e.g. EA)
2. Engineering (Design)
3. Compiling (e.g., DNA sticker model)
4. Copying (e.g., bionics)
5. Analytic/Proof
Approaches
• Optimization (e.g. EA or „Trial and Error“)
Evolving self-organizing systems is difficult.E.g.: (J. Ziegler / W. Banzhaf)
Approx. 10 functional nodes evolvable
26.08.2010 Jena 22Peter Dittrich - FSU & JCB Jena
Peter Dittrich - FSU & JCB Jena 2326.08.2010 Jena
Approaches
1. Optimization (e.g. EA)
2. Engineering (Design)
3. Compiling (e.g., DNA sticker model)
4. Copying (e.g., bionics)
5. Analytic/Proof
Peter Dittrich - FSU & JCB Jena 2426.08.2010 Jena
Programming by human design requires predictability
MICRO(reaction rules)
MACRO(desired behavior)
Abstraction InstantiationUnderstandCausality
Peter Dittrich - FSU & JCB Jena 2526.08.2010 Jena
Programming by human design requires predictability
MICRO(reaction rules)
MACRO(desired behavior)
Abstraction Instantiation“A Theory of Emergence”
can only partially
explain the micro-
macro-link
(cf. halting problem)
Peter Dittrich - FSU & JCB Jena 2626.08.2010 Jena
Programming by human design requires predictability
MICRO(reaction rules)
MACRO(desired behavior)
Abstraction Instantiationmany “partial” theories
Overview
1. Why using chemical-like systems?
2. How to find the right chemical program?
3. Example: Maximal independent set problem.
4. Chemical Organization Theory
5. Organization-oriented chemical programming
6. Evolved vs. manual design
7. Messy Chemistries
8. Outlook: Three Open Problems
26.08.2010 Jena 27Peter Dittrich - FSU & JCB Jena
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 28
Sketch of an Example Application
1. Inject molecules
2. Molecules distribute
3. Cells differentiate (self-organize)
4. A cell is removed
5. Reorganize
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 29
Example: Chemical Program
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
Reactions within a membrane
Transport between
membranes i and j
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 30
Example: MIS chemistry
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
Overview
1. Why using chemical-like systems?
2. How to find the right chemical program?
3. Example: Maximal independent set problem.
4. Chemical Organization Theory
5. Organization-oriented chemical programming
6. Evolved vs. manual design
7. Messy Chemistries
8. Outlook: Three Open Problems
26.08.2010 Jena 31Peter Dittrich - FSU & JCB Jena
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 32
„Chemical Organization“
Organization := a set of molecular species that is(algebraically) closed andself-maintaining
Reaction inside the organization produce only species of that
organization.
Within a self-maintaining set, all species consumed by a reaction
can be produced by a reaction within the self-maintzaining set while no species concentration in the set decreases.
[Speroni di Fenizio/Dittrich (2005/7, Bull. Math. Biol. 2007) inspired by Fontana, Buss, Rössler, Eigen, Kauffman, Maturana, Varela, Uribe]
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 33
Practical View
1
32
4
Chemical Organization
Theory
OrganizationsReaction network
1
32
4
Organization
[P. Dittrich, P. Speroni di Fenizi, Chemical Organization Theory, Bull. Math. Biol., 2007]
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 34
Practical View
{1}
{2, 3}
{1,2,3,4}
{ }
Hasse diagram of organizations
OrganizationsReaction network
Chemical Organization
Theory1
32
4
[P. Dittrich, P. Speroni di Fenizi, Chemical Organization Theory, Bull. Math. Biol., 2007]
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 35
Practical View
1
32
4
Thoerie chemischer
Organization{1}
{2, 3}
{1,2,3,4}
{ }
Dynamics
[2]
[3]
[4][1]
Chemical Organization
Theory
Hasse diagram of organizations
OrganizationsReaction network
[P. Dittrich, P. Speroni di Fenizi, Chemical Organization Theory, Bull. Math. Biol., 2007]
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 36
1. Example: MIS chemistry
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 37
„Chemical Organization“
Organization := a set of molecular species that is(algebraically) closed andself-maintaining
Reaction inside the organization produce only species of that
organization.
Within a self-maintaining set, all species consumed by a reaction
can be produced by a reaction within the self-maintzaining set while no species concentration in the set decreases.
[Speroni di Fenizio/Dittrich (2005/7, Bull. Math. Biol. 2007) inspired by Fontana, Buss, Rössler, Eigen, Kauffman, Maturana, Varela, Uribe]
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 38
1. Example: MIS chemistry
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 39
1. Example: MIS chemistry
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 40
1. Example: MIS chemistry
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 41
1. Example: MIS chemistry
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
The empty organization
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 42
Example 1
d
c
a
b
e
-> a
2
a + b -> 2 b
2
a + c -> 2 c
b -> d
c -> d
b + c -> e
a ->b ->c ->d ->e ->
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 43
Example 1
d
c
a
b
e
2
2
Organization {a, b, d}
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 44
Checking for Closure
d
c
a
b
e
2
2
Organization {a, b, d}
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 45
Checking for Self-Maintenance
d
c
a
b
e
2
2
Organization {a, b, d}
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 46
Checking for Self-Maintenance
d
c
a
b
e
2
2
Organization {a, b, d}
1. Find flux vector
0 0
00
0
outside of org. = 0
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 47
Checking for Self-Maintenance
d
c
a
b
e
2
2
Organization {a, b, d}
0 0
00
0
1. Find flux vector
outside of org. = 0
inside of org. > 01
1
1
10
9 8
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 48
Checking for Self-Maintenance
d
c
a
b
e
2
2
Organization {a, b, d}
1. Find flux vector
0 0
00
0
outside of org. = 0
inside of org. > 01
1
1
10
9 8
2. Check production rates
outside of org. = 0 (closure)
0
0
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 49
Checking for Self-Maintenance
d
c
a
b
e
2
2
Organization {a, b, d}
1. Find flux vector
0 0
00
0
outside of org. = 0
inside of org. > 01
1
1
10
9 8
2. Check production rates
outside of org. = 0 (closure)
0
0
7
inside of org. 0 (self-maint.)
0
0
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 50
All Organizations
d
c
a
b
e
2
2
All Organizations
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 51
All Organizations
d
c
a
b
e
2
2
All Organizationen
a
a
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 52
All Organizations
All Organizations
d
c
a
b
e
2
2a b d
a
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 53
All Organizations
All Organizations
a b d
d
c
a
b
e
2
2a c d
a
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 54
All Organizations
a b d a c d
d
c
a
b
e
2
2
a b c d e
a
Hasse diagram of organizations
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 55
„Overlapping Hierachy“
a b d a c d
d
c
a
b
e
2
2
a b c d e
a
Hasse diagram of organizations
Generate Organization GO(A) from a set A
• GO(A) = GSM(GCl(A))
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 56
Union and Intersection of Organizations
• GO(O1 U O2)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 57
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 58
„Overlapping Hierachy“
a b d a c d
d
c
a
b
e
2
2
a b c d e
a
Hasse diagram of organizations
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 59
DYNAMICS
Assumption: (Feinberg Condition)
0:)( species allfor 0)(
)(
ir xrLHSiv
Nv
x
xx
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 60
Theorem: Fixed points are instances of organizations
a b d a c d
a b c d e
a
)(xx Nv
][
][
][
][
][
e
d
c
b
a
x
)(0 0xNv
0
11
0
7
4
0x
differential equation
fixed point / (stationary solution)
Hasse diagram of organizations
{ a, b, d }
a b d
Dittrich/Speroni d.F., Bull. Math. Biol., 2007
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 61
Limit Set Theorem
Given a state x’ and its limit set L,
now take a state x from the limit set
and take the set of species that have strictly positive concentrations
Is this set an organization?
If it is minimal, definitely yes.
If not, we do not know, but no counterexample, yet.[Stephan Peter 2009/10, paper to be submitted]
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 62
Organizational Analysis in Space
a. Global Analysis• considers a concrete global topology, as
shown before
b. Local Analysis• all possible local environments are
represented by inflow and outflow reactions.
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 63
Global Analysis
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 64
1. Example: MIS simulation
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 65
Organizational Analysis in Space
a. Global Analysis• considers a concrete global topology, as
shown before
b. Local Analysis• all possible local environments are
represented by inflow and outflow reactions.
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 66
Local Analysis
local environment is modeled by inflow and outflow
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
no neighbors
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 67
Local Analysis
local environment is modeled by inflow and outflow
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
no neighbors one “0” neighbors
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 68
2.c Local Analysis
local environment is modeled by inflow and outflow
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
Overview
1. Why using chemical-like systems?
2. How to find the right chemical program?
3. Example: Maximal independent set problem.
4. Chemical Organization Theory
5. Organization-oriented chemical programming
6. Evolved vs. manual design
7. Messy Chemistries
8. Outlook: Three Open Problems
26.08.2010 Jena 69Peter Dittrich - FSU & JCB Jena
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 70
Organization-Oriented Chemical Programming
Computation should be understood as a transition between organizations.
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 71
Seven Principles for Organization-Oriented Chemical Programming
P1: There should be one organization for each output behavior class
P2: The result should be in the closure of the input.
P3: The input should generate the organization representing the desired output
P4: Eliminate organizations not representing a desired output
P5: An output organization should have no organization below
P6: Assure, if possible, stoichiometrically the stability of an output organization
P7: Use kinetic laws for fine tuning
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
Overview
1. Why using chemical-like systems?
2. How to find the right chemical program?
3. Example: Maximal independent set problem.
4. Chemical Organization Theory
5. Organization-oriented chemical programming
6. Evolved vs. manual design
7. Messy Chemistries
8. Outlook: Three Open Problems
26.08.2010 Jena 72Peter Dittrich - FSU & JCB Jena
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 73
Chemical Flip-Flop: A controllable bi-stable chemical
system
Reaction network
cDA
CdA
CDa
Cda
dCB
DcB
DCb
Dcb
0
0
0
0
Dd
Cc
Bb
Aa
256 possible sets of molecular species
Cf. Matsumaru et. al
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 74
Organizations for different inflows
Cf. Matsumaru et. al
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 75Cf. Matsumaru et. al
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 76
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 77
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 78
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 79Cf. Matsumaru et. al
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 80
Evolution vs. manual design Example: Chemical Flip-Flop
[2] T. Lenser, N. Matsumaru, T. Hinze, P. Dittrich. Tracking the Evolution of Chemical Computing Networks. In S. Bullock, J. Noble, R. Watson, M.A. Bedau (Eds.), Proc. of Artificial Life XI, pp. 343-350, MIT Press, 2008
[3] N. Matsumaru, T. Lenser, F. Centler, P. Speroni di Fenizio, T. Hinze, and P. Dittrich, Common organizational structures within two chemical flip-flop, Proceeding of International Workshop on Natural Computing, 2008
evolved manually designed
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 81
3. Evolution vs. manual design
[2] T. Lenser, N. Matsumaru, T. Hinze, P. Dittrich. Tracking the Evolution of Chemical Computing Networks. In S. Bullock, J. Noble, R. Watson, M.A. Bedau (Eds.), Proc. of Artificial Life XI, pp. 343-350, MIT Press, 2008
[3] N. Matsumaru, T. Lenser, F. Centler, P. Speroni di Fenizio, T. Hinze, and P. Dittrich, Common organizational structures within two chemical flip-flop, Proceeding of International Workshop on Natural Computing, 2008
evolved manually designed
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 82
3. Evolutionary Process: Fitness
[2] T. Lenser, N. Matsumaru, T. Hinze, P. Dittrich. Tracking the Evolution of Chemical Computing Networks. In S. Bullock, J. Noble, R. Watson, M.A. Bedau (Eds.), Proc. of Artificial Life XI, pp. 343-350, MIT Press, 2008
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 83
3. Evolutionary Process: Number of Organizations
halt input
reset input
set input
[2] T. Lenser, N. Matsumaru, T. Hinze, P. Dittrich. Tracking the Evolution of Chemical Computing Networks. In S. Bullock, J. Noble, R. Watson, M.A. Bedau (Eds.), Proc. of Artificial Life XI, pp. 343-350, MIT Press, 2008
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 84
3. Evolutionary Process: Average Number of Organizations
halt input
reset inputset input
[2] T. Lenser, N. Matsumaru, T. Hinze, P. Dittrich. Tracking the Evolution of Chemical Computing Networks. In S. Bullock, J. Noble, R. Watson, M.A. Bedau (Eds.), Proc. of Artificial Life XI, pp. 343-350, MIT Press, 2008
Overview
1. Why using chemical-like systems?
2. How to find the right chemical program?
3. Example: Maximal independent set problem.
4. Chemical Organization Theory
5. Organization-oriented chemical programming
6. Evolved vs. manual design
7. Messy Chemistries
8. Outlook: Three Open Problems
26.08.2010 Jena 85Peter Dittrich - FSU & JCB Jena
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 86
Messy Chemistries: Organizational Evolution
current state(concentration vector)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 87
Organizational Evolution
set of species present
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 88
Organizational Evolutiongenerate organization
Overview
1. Why using chemical-like systems?
2. How to find the right chemical program?
3. Example: Maximal independent set problem.
4. Chemical Organization Theory
5. Organization-oriented chemical programming
6. Evolved vs. manual design
7. Messy Chemistries
8. Outlook: Three Open Problems
26.08.2010 Jena 89Peter Dittrich - FSU & JCB Jena
Outlook: Three Open Problems
1. How to design chemical-like programs?
2. Where do they perform well?
3. What is an ideal chemical language?
26.08.2010 Jena 90Peter Dittrich - FSU & JCB Jena
Acknowledgements
Pietro Speroni di Fenizio, Naoki Matsumaru,Florian Centler, Christoph Kaleta, Christian Knüpfer, Thorsten Lenser, Thomas Hinze, Dennis Görlich, Gabi
Escuela, Maiko Lohel, Stefan Artmann, Clemens Beckstein, Stephan Diekmann
Funding: BMBF, EU (FP6, FP7), DFG, RLS, DAAD, JSMC (DFG), HIGRADE
Friedrich-Schiller-Universität Jena Jena Centre for Bioinformatics
Commercial: We are looking for Postdocs in
organic & chemical computing and cell cycle modeling
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 92
1. Example: Maximum Independent Set Problem (MIS)
• New chemical algorithm– only four species– no distinction of neighbors required
[1] N. Matsumaru, T. Hinze, and P. Dittrich. Organization-oriented chemical programming for Distributed ArtifactsInternational Journal of Nanotechnology and Molecular Computation (submitted)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 93
4. Simulator for Quantitative Evaluation of Distributed Chemical
Computing• Specify chemical program by a set of
explicit reaction rules• Specify topology by a graph• Run stochastic simulation• Visualize dynamics
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 94
4. Simulator for Quantitative Evaluation of Distributed Chemical
Computing
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 95
4. Looking at the dynamics of one node (V2)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 96
4. Simulator for Quantitative Evaluation of Distributed Chemical
Computing
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 97
5. Organization Oriented Chemical Computing for Artificial Development
• OO-ChemProg applied to cell differentiation / morphogenesis
• Differentiation can be understood as a transition between organizations
-> might be useful inArtificial Development + Evolution
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 98
6. Emergent Control
(manuscript in preparation)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 99
6. Feed back control is everywhere
Source: http://upload.wikimedia.org/wikipedia/en/4/40/Feedback_loop.JPG
s
6. Emergent Control
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 101
6. Architecture for Emergent Control
macro-to-microtranslator
system to be controlledfeedforward controller
mic
ro
level
macro
le
vel
macro goals
micro rules or
downward causation
desired macro
behavior(manuscript in preparation)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 102
6. Architecture for Emergent Control
macro-to-microtranslator
system to be controlledfeedforward controller
mic
ro
level
macro
le
vel
macro goals
micro rules or
downward causation
desired macro
behavior(manuscript in preparation)
feedback dynamics
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 103
6. Current Situation
macro-to-microtranslator
system to be controlledfeedforward controller
mic
ro
level
macro
le
vel
macro goals micro rules
desired macro
behavior(manuscript in preparation)
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6. Strategies for Building a Macro-to-Micro Translator
• Manual “intelligent” design, Policies• Evolution (optimization, playing, etc)• Theory• Mimicking• Compiling• Experiment and numerical inversion
(manuscript in preparation)
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6. In practical applications, emergent control will often be
combined with feedback control.
macro-to-microtranslator
system to be controlledfeedforward controller
mic
ro
level
macro
le
vel
(manuscript in preparation)
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6. Emergent Control Examples Studied
a. Balance the number of particles of two types
b. Control the number of clusters in a population of evolving entities.
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6.A Example: Balance the number of particles of two
types
Peter Dittrich - FSU & JCB Jena
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6.A Example: Recovery Time
feedback control
emergent control
Time (arbitrary units)
Peter Dittrich - FSU & JCB Jena
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6.A Example: Cost
feedback control
emergent control
Time (arbitrary units)
Cost (arbitracy units)
Peter Dittrich - FSU & JCB Jena
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6. Emergent Control Conclusions
• Emergent control is fundamentally different from feedback control.
• In emergent control it is more difficult to consider the user’s demands.– There are various approaches, but no satisfying (i.e. general enough) macro-
to-micro translators yet.
• Emergent control appears to be more costly.• Macro-level models of the dynamics are not
enough for quantitative evaluation.• a powerful abstraction of emergent (self-
organizing) control is needed.
II. Outlook Phase III
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II. Outlook Phase III
1. Controlled emergent control
2. Structured molecules
3. Application scenarios: “chemical” middleware and sensor net
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Towards a Chemical Middleware (with Augsburg)
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II. Outlook Phase III
1. Controlled emergent control
2. Structured molecules
3. Application scenarios: “chemical” middleware and sensor net
4. Bringing European community of “chemical-like OC” together. European Mini Workshop (April 2010)
- very focused, in-silico only- How to design/program?- Quantitative evaluation?
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Acknowledgement & Jobs
• Thorsten Lenser• Christoph Kaleta• Pietro Speroni di Fenizio• Gabi Escuela Funding: DFG
We are looking for Postdocs and Phd students in in-silico chemical computing (DFG, OC SPP) and in-vivo chemical computing (EU, FP7, CHEM-IT). Contact: Peter Dittrich (di.ttri.ch)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 116
1st phase : primaryRefereed Journal:[1] Naoki Matsumaru, Florian Centler, Pietro Speroni di Fenizio, and Peter Dittrich.Chemical Organization Theory as a Theoretical Base for Chemical Computing.International Journal of Unconventional Computing, 3(4):285{309, 2007
Book Chapter:[2] Naoki Matsumaru, Thorsten Lenser, Thomas Hinze, and Peter Dittrich.Toward Organization-Oriented Chemical Programming: A Case Study with theMaximal Independent Set Problem.In F. Dressler and I. Carreras, editors, Advances in Biologically Inspired InformationSystems, volume 69 of Studies in Computational Intelligence, pages 147{163. Springer,Berlin, 2007
Refereed Proceedings:[3] Peter Dittrich and Naoki Matsumaru.Organization-Oriented Chemical Programming.In 7th International Conference on Hybrid Intelligent Systems (HIS), IEEE ConferenceProceedings, pages 18{23. IEEE, 2007[4] Naoki Matsumaru and Peter Dittrich.Organization-oriented chemical programming for the organic design of distributedcomputing systems.In 1st international conference on bio inspired models of network, information and com-puting systems (BIONETICS), volume 275 of ACM International Conference Proceeding,Cavalese, Italy, 2006. IEEE.also available at http://www.x-cd.com/bionetics06cd/[5] Naoki Matsumaru, Pietro Speroni di Fenizio, Florian Centler, and Peter Dittrich.On the Evolution of Chemical Organizations.In Stefan Artmann and Peter Dittrich, editors, Explorations in the complexity of possiblelife: abstracting and synthesizing the principles of living systems, Proceedings of the 7thGerman Workshop of Articial Life, pages 135{146. Aka, Berlin, 2006[6] Naoki Matsumaru, Florian Centler, and Peter Dittrich.Chemical Organization Theory as a Theoretical Base for Chemical Computing.In Christof Teuscher and Andrew Adamatzky, editors, Proceedings of the 2005 Work-shop on Unconventional Computing: From Cellular Automata to Wetware, pages 75{88.Luniver Press, Beckington, UK, 2005[7] Peter Dittrich.The Bio-Chemical Information Processing Metaphor as a ProgrammingParadigm for Organic Computing.In U. Brinkschulte, J. Becker, C. Hochberger, T. Martinetz, C. Muller-Schloer,�H. Schmeck, T. Ungerer, and R. Wurtz, editors, ARCS '05 - 18th International�Conference on Architecture of Computing Systems 2005, pages 95{99. VDE Verlag,Berlin, 2005[8] Peter Dittrich.Chemical Computing.In Jean-Pierre Ban^atre, Pascal Fradet, Jean-Louis Giavitto, and Olivier Michel, editors,Unconventional Programming Paradigms, International Workshop UPP 2004, Le MontSaint Michel, France, September 15-17, 2004, Revised Selected and Invited Papers,volume 3566 of LNCS, pages 19{32. Springer, Berlin, 2005
Refereed (Extended) Abstract:[9] Naoki Matsumaru, Thorsten Lenser, Thomas Hinze, and Peter Dittrich.Designing a Chemical Program using Chemical Organization Theory.BMC Systems Biology, 1(Suppl 1):P26, 2007.from BioSysBio 2007: Systems Biology, Bioinformatics, and Synthetic Biology, Manchester,UK, 11-13 January 2007
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1st phase: secondaryRefereed Journal:[10] Christoph Kaleta, Florian Centler, and Peter Dittrich.Analyzing Molecular Reaction Networks: From Pathways to Chemical Organizations.Mol. Biotechnol., 34(2):117{123, 2006[11] Naoki Matsumaru, Florian Centler, Pietro Speroni di Fenizio, and Peter Dittrich.Chemical organization theory applied to virus dynamics.it - Information Technology, 48(3):154{160, 2006
Refereed Proceedings:[12] Florian Centler, Pietro Speroni di Fenizio, Naoki Matsumaru, and Peter Dittrich.Chemical organizations in the central sugar metabolism of Escherichia Coli.In Mathematical Modeling of Biological Systems, Volume I. A Birkhauser book, 2007�[13] Naoki Matsumaru, Pietro Speroni di Fenizio, Florian Centler, and Peter Dittrich.A Case Study of Chemical Organization Theory Applied to Virus Dynamics.In Jan T. Kim, editor, Systems Biology Workshop at ECAL 2005, Workshop ProceedingsCD-ROM, Kent, UK, 2005[14] Thomas Hinze, Raael Faler, Thorsten Lenser, Naoki Matsumaru, and PeterDittrich.Ezient chemisch rechnen durch deterministische Reaktionssysteme mitRegelpriorisierung.In M. Droste and M. Lohrey, editors, Proceedings of 17. Theorietag Automaten undFormale Sprachen, pages 68{73. Universitat Leipzig, 2007�[15] Thomas Hinze, Sikander Hayat, Thorsten Lenser, Naoki Matsumaru, and PeterDittrich.Hill Kinetics Meets P Systems: A Case Study on Gene Regulatory Networksas Computing Agents in silico and in vivo.In G. Eleftherakis, P. Kefalas, and G. Paun, editors, Proceedings of the Eight Workshopon Membrane Computing (WMC8), pages 363{381. SEERC Publishers, 2007[16] Thomas Hinze, Sikander Hayat, Thorsten Lenser, Naoki Matsumaru, and Peter Dittrich.Hill Kinetics Meets P Systems.In G. Eleftherakis, P. Kefalas, G. Paun, G. Rozenberg, and A. Salomaa, editors, Mem-brane Computing, volume 4860 of LNCS, pages 320{335. Springer Verlag, 2007Refereed (Extended) Abstract[17] Peter Dittrich, Thomas Hinze, Bashar Ibrahim, Thorsten Lenser, and Naoki Matsumaru.Hierarchically Evolvable Components for Complex Systems: Biologically InspiredAlgorithmic Design.In J. Jost, D. Helbing, H. Kantz, and A. Deutsch, editors, Proceedings of the EuropeanConference on Complex Systems (ECCS2007), page 85. TU Dresden, 2007
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2nd phase: primaryRefereed Journal:[1] N. Matsumaru, T. Hinze, and P. Dittrich.Organization-oriented chemical programming for MIS problem.International Journal of Nanotechnology and Molecular Computation (submitted)
Refereed Proceedings:[2] T. Lenser, N. Matsumaru, T. Hinze, P. Dittrich. Tracking the Evolution of Chemical Computing Networks. In S. Bullock, J. Noble, R. Watson, M.A. Bedau (Eds.), Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems (Artificial Life XI), ISBN 978-0-262-75017-2, pp. 343-350, MIT Press, 2008
[3] N. Matsumaru, T. Lenser, F. Centler, P. Speroni di Fenizio, T. Hinze, and P. Dittrich,Common organizational structures within two chemical flip-flop, Proceeding of International Workshop on Natural Computing, 2008
Dissertation:[4] N. Matsumaru
Chemical Programming to Exploit Chemical Reaction Systems for Computation, Friedrich-Schiller-University Jena (submitted on June)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 119
2nd phase: SecondaryRefereed Journal:[5]. C. Kaleta, F. Centler, P Speroni di Fenizio, P. Dittrich : Phenotype prediction in regulated metabolic networks, BMC Systems Biology 2008, 2:37 (25 April 2008)[6] B. Ibrahim , S. Diekmann, E. Schmidt, P. Dittrich : In--Silico Modling of the Mitotic Spindle Assembly Check point, PLoS ONE 3(2):e 1555, 2008[7]. F. Centler, C. Kaleta, P. Speroni di Fenizio, P. Dittrich : Computing Chemical Organizations in Biological Networks Bioinformatics, 24: 1611-1618, 2008
Refereed Proceedings:[8] T. Hinze, R. Fassler, T. Lenser, N. Matsumaru, P. Dittrich. Event-Driven Metamorphoses of P Systems. In P. Frisco, D.W. Corne, G. Paun (Eds.), Prel. Proceedings Ninth International Workshop on Membrane Computing (WMC9), pp. 209-225, Heriot-Watt University, accepted for publication in Series Lecture Notes in Computer Science, Springer Verlag, 2008[9] T. Hinze, S. Hayat, T. Lenser, N. Matsumaru, P. Dittrich : Biosignal--Based Computing by AHHL Induced Synthetic Gene Regulatory Networks. In Proc. of the FirstInternational Conference on Bio-Inspired Systems and Signal Processing (BIOSIGNALS2008), Vol. 1, pp. 162-169 , IEEE Engineering in Medicine and Biology Society, Institute for Systems and Technologies of Information Control and Communication, INSTICC press, 2008
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 120
Motivation
(1) Every biological life form processes
information on a chemical level.
(2) Bio-chemical information processing
posses a series of valuable self-x properties
CHemical Abstract Machine
(3) Chemical programming appears to
be difficult.
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Aim
How to program chemical-like systems?
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 122
Challenge
MICRO(reaction rules)
MACRO(desired behavior)
Understand
Causality
[12] Peter Dittrich. Chemical Computing. In J.-P. Banatre, J.-L. Giavitto, P. Fradet, and O. Michel (Eds.), Unconventional Programming Paradigms (UPP 2004), LNCS, 3566: 19-32. Springer, Berlin, 2005
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 123
Results
1. Chemical Programming Paradigm
2. Programming Environment
3. Case Studies and Evaluation
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 124
1. Chemical Programming Paradigm
“Organization Oriented Programming”
Computation should appear as a movement within the set of organizations.
[5] P. Dittrich, N. Matsumaru,Organization-Oriented Chemical Programming, In: Proc. of 7th International Conference on Hybrid Intelligent Systems (HIS 2007), IEEE DL, 6 pages, 2007, (in print)
[2] N. Matsumaru, T. Lenser, T. Hinze, and P. Dittrich.Designing a Chemical Program using Chemical Organization Theory.BMC Systems Biology, 1(Suppl 1):P26, 2007, (extended abstract)
[11] Peter Dittrich.The Bio-Chemical Information Processing Metaphor as a ProgrammingParadigm for Organic Computing. In U. Brinkschulte, J. Becker, C. Hochberger, T. Martinetz, C. Mueller-Schloer, H. Schmeck, T. Ungerer, and R. Wuertz, editors, ARCS '05 - 18th International Conference on Architecture of Computing Systems 2005, pages 96-100. VDE Verlag, Berlin, 2005
[12] Peter Dittrich. Chemical Computing. In J.-P. Banatre, J.-L. Giavitto, P. Fradet, and O. Michel (Eds.), Unconventional Programming Paradigms (UPP 2004), LNCS, 3566: 19-32. Springer, Berlin, 2005
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 125
Practical View
1
32
4
Chemical Organization
Theory
OrganizationsReaction network
1
32
4
Organization
[P. Dittrich, P. Speroni di Fenizi, Chemical Organization Theory, Bull. Math. Biol., 2007]
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 126
Practical View
{1}
{2, 3}
{1,2,3,4}
{ }
Hasse diagram of organizations
OrganizationsReaction network
Chemical Organization
Theory1
32
4
[P. Dittrich, P. Speroni di Fenizi, Chemical Organization Theory, Bull. Math. Biol., 2007]
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 127
Practical View
1
32
4
Thoerie chemischer
Organization{1}
{2, 3}
{1,2,3,4}
{ }
Dynamics
[2]
[3]
[4][1]
Chemical Organization
Theory
Hasse diagram of organizations
OrganizationsReaction network
[P. Dittrich, P. Speroni di Fenizi, Chemical Organization Theory, Bull. Math. Biol., 2007]
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 128
Organization Oriented Design Principles
1. For each solution there must be (at least) one organization containing the desired output molecules.
2. Eliminate as many other organizations as possible.
3. There must be a pathway from the input set to the desired organization.
4. The set of input molecules must generate an organization containing the target organization.
5. Make sure that the target organization is stable from a stoichiometric point of view.
[5] P. Dittrich, N. Matsumaru,Organization-Oriented Chemical Programming, In: Proc. of 7th International Conference on Hybrid Intelligent Systems (HIS 2007), IEEE DL, 6 pages, 2007, (in print)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 129
2. Programming Environment
• Analysis– Static, structural (OrgAnalyszer) (FluxAnalyzer)– Dynamical (ODESolver) (Copasi)
• Programming– List of reaction rules (Text editor)– Network structure (CellDesigner.org)
• Protocols
(SBW)– Data format (SBML)
N. Matsumaru, P. Dittrich,CHEMORG I, Project Report, FSU Jena, 2007
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3. Evaluation and Case Studies
a. Logic gates(e.g., chemical xor)
b. Boolean networks (e.g., chemical flip-flop)
c. Maximum independent set
[1] N. Matsumaru, F. Centler, P. Speroni di Fenizio, and P. Dittrich.Chemical Organization Theory as a Theoretical Base for Chemical Computing.International Journal on Unconventional Computing, 28 pages, 2007, (in print)
[4] N. Matsumaru, T. Lenser, T. Hinze, P. Dittrich,Toward Organization-Oriented Chemical Programming: a case study with the maximal independent set problem. In F. Dressler and I. Carreras (Eds.), Advances in Biologically Inspired Information Systems, SCI, 69: 147-163, Springer, Berlin, 2007
[6] N. Matsumaru and P. Dittrich.Organization-oriented chemical programming for the organic design of distributed computing systems. In Proc.of Bionetics, Cavalese, Italy, December 11-13, 7 pages, IEEE, 2006.
[9] N. Matsumaru, F. Centler, and P. Dittrich.Chemical Organization Theory as a Theoretical Base for Chemical Computing.In C. Teuscher and A. Adamatzky, editors, Workshop on Unconventional Computing, p. 71-82. Luniver Press, Beckington, 2005
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 133
0
0
0
Cc
Bb
Aa
cBA
CbA
CBa
cba
1
ca b0
1
00
0
0
0
1 1
1
1
Chemical XOR
A
a : a == 0
: a == 1
[1] N. Matsumaru, F. Centler, P. Speroni di Fenizio, and P. Dittrich.Chemical Organization Theory as a Theoretical Base for Chemical Computing.International Journal on Unconventional Computing, 28 pages, 2007, (in print)
[9] N. Matsumaru, F. Centler, and P. Dittrich.Chemical Organization Theory as a Theoretical Base for Chemical Computing.In C. Teuscher and A. Adamatzky, editors, Workshop on Unconventional Computing, p. 71-82. Luniver Press, Beckington, 2005
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 134
Chemical XOR (two inputs)
Organizations
Chemical Organization
Theory
cBA
CbA
CBa
cba
64 possible sets of molecular species1 is an organization
0
0
0
Cc
Bb
Aa
a0 B0
{ a, B, C }
[1] Matsumaru, N. et al. Int. J. Unconv. Comp., 2007 (in print)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 135
Chemical XOR (with one input)
Organizations
Reaction network
Chemical Organization
Theory
cBA
CbA
CBa
cba
64 possible sets of molecular species3 are an organization
0
0
0
Cc
Bb
Aa
a0[1] Matsumaru, N. et al. Int. J. Unconv. Comp., 2007 (in print)
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 136
Chemical Flip-Flop (with two inputs)
[1] N. Matsumaru, F. Centler, P. Speroni di Fenizio, and P. Dittrich.Chemical Organization Theory as a Theoretical Base for Chemical Computing.International Journal on Unconventional Computing, 28 pages, 2007, (in print)
[9] N. Matsumaru, F. Centler, and P. Dittrich.Chemical Organization Theory as a Theoretical Base for Chemical Computing.In C. Teuscher and A. Adamatzky, editors, Workshop on Unconventional Computing, p. 71-82. Luniver Press, Beckington, 2005
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 137
Maximal Independent Set
• Def. [Independent set]A set of vertices no two of which are adjacent
• Def. [Maximal Independent set]
Given an undirected graph, an independ set is maximal if no vertex can be added to the independent set.
Note: Maximal independent set is different from maximum independent set.
There are two maximal independent sets.
The maximum independent set has the size of 3.
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• Under central daemon [Luby 1985]
• Distributed system [Shukla, et al. 1995]
Algorithms for MIS problem
):.().),Neigh(( FalseIndvTrueIndnvn
):.().),Neigh(( TrueIndvFalseIndnvn
end
Neigh
begin
do 0 while
0 ,
(v))V-({v}-V
V{v} | vII
V
IV,EG
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1
neighbors of:number
000ii
n
lkj snsss
i
Algebraic Chemistry for MIS problem
binis
Membership
Vertex ID
to the inde-
}),(|{ 01 Evvss jiij
010 ii ss
},,1|,{ 10 Niss ii M
N
i
i
1
RR
pendent set
[4] N. Matsumaru, T. Lenser, T. Hinze, P. Dittrich, SCI , 69:147-163, Springer, Berlin, 2007
[6] N. Matsumaru and P. Dittrich., Proc.of Bionetics, 2006.
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 140
Algebraic Chemistry for MIS problem
12
03
01
02
13
02
11
2sss
ss
ss
11
02
01
12
ss
ss
} s, s, s, s, s, s{ 13
03
12
02
11
01M
13
02
03
12
ss
ss
0
0
0
13
03
12
02
11
01
ss
ss
ss
Undirected GraphReaction Network
Organizational structure
[4] N. Matsumaru, T. Lenser, T. Hinze, P. Dittrich, SCI , 69:147-163, Springer, Berlin, 2007
[6] N. Matsumaru and P. Dittrich., Proc.of Bionetics, 2006.
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„Chemical Organization“
Organization := a set of molecules that is(algebraically) closed andself-maintaining
There is no reaction producingany other molecules
than the member of the set.
Within the set, all moleculesconsumed by a reaction
can be reproduced by a reaction.
[P. Dittrich, P. Speroni di Fenizi, Chemical Organization Theory, Bull. Math. Biol., 2007]
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Algebraic Chemistry for MIS problem
12
03
01
02
13
02
11
2sss
ss
ss
11
02
01
12
ss
ss
} s, s, s, s, s, s{ 13
03
12
02
11
01M
13
02
03
12
ss
ss
0
0
0
13
03
12
02
11
01
ss
ss
ss
Undirected GraphReaction Network
Organizational structure
There is no reaction producingany other molecules
than the member of the set.
}s{ 12
[4] N. Matsumaru, T. Lenser, T. Hinze, P. Dittrich, SCI , 69:147-163, Springer, Berlin, 2007
[6] N. Matsumaru and P. Dittrich., Proc.of Bionetics, 2006.
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 143
Algebraic Chemistry for MIS problem
12
03
01
02
13
02
11
2sss
ss
ss
11
02
01
12
ss
ss
} s, s, s, s, s, s{ 13
03
12
02
11
01M
13
02
03
12
ss
ss
0
0
0
13
03
12
02
11
01
ss
ss
ss
Undirected GraphReaction Network
Organizational structure
There is no reaction producingany other molecules
than the member of the set.
},s{ 03
12 s
Within the set, all moleculesconsumed by a reaction
can be reproduced by a reaction.
[4] N. Matsumaru, T. Lenser, T. Hinze, P. Dittrich, SCI , 69:147-163, Springer, Berlin, 2007
[6] N. Matsumaru and P. Dittrich., Proc.of Bionetics, 2006.
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 144
Organizational structure
Algebraic Chemistry for MIS problem
12
03
01
02
13
02
11
2sss
ss
ss
11
02
01
12
ss
ss
} s, s, s, s, s, s{ 13
03
12
02
11
01M
13
02
03
12
ss
ss
0
0
0
13
03
12
02
11
01
ss
ss
ss
Undirected GraphReaction NetworkThere is no reaction producing
any other molecules than the member of the set.
Within the set, all moleculesconsumed by a reaction
can be reproduced by a reaction.
[4] N. Matsumaru, T. Lenser, T. Hinze, P. Dittrich, SCI , 69:147-163, Springer, Berlin, 2007
[6] N. Matsumaru and P. Dittrich., Proc.of Bionetics, 2006.
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 145
Organizational structure
Algebraic Chemistry for MIS problem
12
03
01
02
13
02
11
2sss
ss
ss
11
02
01
12
ss
ss
} s, s, s, s, s, s{ 13
03
12
02
11
01M
13
02
03
12
ss
ss
0
0
0
13
03
12
02
11
01
ss
ss
ss
Undirected GraphReaction Network
[4] N. Matsumaru, T. Lenser, T. Hinze, P. Dittrich, SCI , 69:147-163, Springer, Berlin, 2007
[6] N. Matsumaru and P. Dittrich., Proc.of Bionetics, 2006.
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 146
} s, s, s, s, s, s{ 13
03
12
02
11
01M
Algebraic Chemistry for MIS problem
0
0
0
13
03
12
02
11
01
ss
ss
ss
12
03
01
02
13
02
11
2sss
ss
ss
11
03
02
01
13
01
12
2sss
ss
ss
13
02
01
03
12
03
11
2sss
ss
ss
[4] N. Matsumaru, T. Lenser, T. Hinze, P. Dittrich, SCI , 69:147-163, Springer, Berlin, 2007
[6] N. Matsumaru and P. Dittrich., Proc.of Bionetics, 2006.
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Algebraic Chemistry for MIS problem
Undirected graph Organizational structure
Reaction network
MR
:12 molecular species
:32 reaction rules
1v2v
3v
5v
6v
4v
[4] N. Matsumaru, T. Lenser, T. Hinze, P. Dittrich, SCI , 69:147-163, Springer, Berlin, 2007
[6] N. Matsumaru and P. Dittrich., Proc.of Bionetics, 2006.
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Current and Future Work
1. Structured Molecules
2. Quantitative Evaluation
3. Demonstrator (sensor network scenario)
4. Intrinsic vs. Extrinsic Self-Organization
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 149
1. Structured Molecules
Example: implicitly defined molecules
M = { 0, 1, 2, 3, …, }
Example: implicitily defined reaction rules
a + b c with c = a + b mod 4711
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1. Candidates to be evaluated
• Bit strings and Boolean expressions• Patter matching• Interacting finite state machines• Scheme• String-based P-systems• Fraglets
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1. Preliminary Study of 32-bit-Sized Interacting Machines
[8] N. Matsumaru, P. Speroni di Fenizio, F. Centler, and P. Dittrich.On the Evolution of Chemical Organizations. In S. Artmann and P. Dittrich (Eds.), Proc. of the 7th German Workshop of Articial Life, p.135-146, IOS Press, Amstterdam, 2006
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 152
1. Structured Molecules: Fraglets
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 153
2. Quantitative Evaluation
• Robustnesse.g., probability of failure after perturbation
• Efficiency of self-organizatione.g., transient time until desired result appears
• ScalabilityHow do robustness and efficiency scale with system/problem size?
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 154
2. Benchmark Problem
1. Inject molecules
2. Molecules distribute
3. Cells differentiate (self-organize)
4. A cell is removed
5. Reorganize
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 155
Benchmark Problem
1. Inject molecules
2. Molecules distribute
3. Cells differentiate (self-organize)
4. A cell is removed
5. Reorganize
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 156
3. Demonstrator
• Real sensor network
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 157
4. Intrinsic vs. Extrinsic Self-Organization
• Focus so far: How to program?
• In this WP: How to control?
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Space
[P. Speroni di Fenizi, P. Dittrich, Chemical Organizations at Different Spatial Scales, LNCS, Springer, 2007]
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Evolutionary Design
http://www.esignet.net
[T. Lenser, T. Hinze, P. Dittrich, LNCS, Springer, 2007]
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 160
Final Remarks
• Mini-Workshop on chemical-like/particle based organic computing approaches.
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References & Acknowledgement
Refereed Journal:[1] N. Matsumaru, F. Centler, P. Speroni di Fenizio, and P. Dittrich.Chemical Organization Theory as a Theoretical Base for Chemical Computing.International Journal on Unconventional Computing, 28 pages, 2007, (in print)
[2] N. Matsumaru, T. Lenser, T. Hinze, and P. Dittrich.Designing a Chemical Program using Chemical Organization Theory.BMC Systems Biology, 1(Suppl 1):P26, 2007, (extended abstract)
[3] N. Matsumaru, F. Centler, P. Speroni di Fenizio, and P. Dittrich,Chemical organization theory applied to virus dynamicsit - Information Technology, 48(3):154-160, 2006
Refereed Proceedings:[4] N. Matsumaru, T. Lenser, T. Hinze, P. Dittrich,Toward Organization-Oriented Chemical Programming: a case study with the maximal independent set problem. In F. Dressler and I. Carreras (Eds.), Advances in Biologically Inspired Information Systems, SCI, 69: 147-163, Springer, Berlin, 2007
[5] P. Dittrich, N. Matsumaru,Organization-Oriented Chemical Programming, In: Proc. of 7th International Conference on Hybrid Intelligent Systems (HIS 2007), IEEE DL, 6 pages, 2007, (in print)
[6] N. Matsumaru and P. Dittrich.Organization-oriented chemical programming for the organic design of distributed computing systems. In Proc.of Bionetics, Cavalese, Italy, December 11-13, 7 pages, IEEE, 2006.
[7] F. Centler, P. Speronni di Fenizio, N. Matsumaru, and P. Dittrich.Chemical organizations in the central sugar metabolism of Escherichia Coli. In Modeling and Simulation in Science Engineering and Technology, Post-Proceedings of ECMTB 2005, 2007. (in print)
[8] N. Matsumaru, P. Speroni di Fenizio, F. Centler, and P. Dittrich.On the Evolution of Chemical Organizations. In S. Artmann and P. Dittrich (Eds.), Proc. of the 7th German Workshop of Articial Life, p.135-146, IOS Press, Amstterdam, 2006
[9] N. Matsumaru, F. Centler, and P. Dittrich.Chemical Organization Theory as a Theoretical Base for Chemical Computing.In C. Teuscher and A. Adamatzky, editors, Workshop on Unconventional Computing, p. 71-82. Luniver Press, Beckington, 2005
[10] N. Matsumaru, P. Speroni di Fenizio, F. Centler, and P. Dittrich.A Case Study of Chemical Organization Theory Applied to Virus Dynamics.In Jan T. Kim, editor, Systems Biology Workshop at ECAL 2005, Workshop Proceedings CD-ROM, 7 pages, Kent, UK, 2005
[11] Peter Dittrich.The Bio-Chemical Information Processing Metaphor as a ProgrammingParadigm for Organic Computing. In U. Brinkschulte, J. Becker, C. Hochberger, T. Martinetz, C. Mueller-Schloer, H. Schmeck, T. Ungerer, and R. Wuertz, editors, ARCS '05 - 18th International Conference on Architecture of Computing Systems 2005, pages 96-100. VDE Verlag, Berlin, 2005
[12] Peter Dittrich. Chemical Computing. In J.-P. Banatre, J.-L. Giavitto, P. Fradet, and O. Michel (Eds.), Unconventional Programming Paradigms (UPP 2004), LNCS, 3566: 19-32. Springer, Berlin, 2005
Funding: DFG Grant No. Di 852/4-1
26.08.2010 Jena Peter Dittrich - FSU & JCB Jena 162
Story 1. Introduction
2. Organization Oriented Programming
3. Framework for Chemical Programming
4. Case Studies1. Boolean Logic
2. Boolean Networks flip-flop
3. Maximum independent set problem
5. Structured molecules1. Pre-liminary study with artificial chemistry
2. New methods for representation and analysis needed
3. Case studies for evaluation
4. Candidates for molecular structures (fraglets)
6. Quantitative evaluation1. Build on maximum independent set problem
2. Connect to other projects
7. Demonstrator
8. Some theory: Intrinsically vs. Extrinsically self-organizing systems
9. Evolving networks, ESIGNET, Modularization?
10. Summary of Publications
I. Results of Phase II