(-∞) General Background:The Microscopic Representation of Complex Macroscopic Phenomena, , Annual Reviews of Computational Physics II p 243, ed D. Stauffer, World Scientific 1995

Complexity a Science at 30, Europhysics News Feb-March 2003 p54

(-∞) General Background:The Microscopic Representation of Complex Macroscopic Phenomena, , Annual Reviews of Computational Physics II p 243, ed D. Stauffer, World Scientific 1995

Complexity a Science at 30, Europhysics News Feb-March 2003 p54

  

Fig 1 Map of Complexity and its Neighbouring Fields (for a more detailed interactive version see http://complexity.cogniview.com/MapIndex.html )

-1) Realistic Market Modeling Platforms (Lev) A microscopic model of the stock market; Cycles, booms and crashes, Economics Letters 45 (1994) 103-111. Behaviorally realistic simulations of stock markets; Traders with a soul, Computer Physics Communications 121-122 (1999) 161 . http://xxx.lanl.gov/abs/adap-org/9901003Microscopic Simulation of Financial Markets, Academic Press, New York, 2000.

Kahneman-Tversky

Lev Thesis; The string market: Statistical Mechanics of Conventional Traders May Lead to Non-Conventional Market Behavior, Physica Scripta. Vol. T106, 41, 2003

Market 'spikes' are seen by traders as freak events.Physicists expect them, Thursday

October 3, 2002  

Stock market shock explainedPhysicists model recent trading frenzy.

Lev; Frantisek; The Interacting Gaps Model: Physica A 330 (2003) 232. Given offered prices around current price at intervals

Limit orderLimit order (left unsaturated at current price)

Limit order

1 ii nn 1 jj nn

One may have a new limit order close to the current price: changing the price by 1 tick

Limit orderLimit orderLimit order

1 jj nn1 ii nn

Or one may have a new market order that eliminates the order at the current price and goes to the first neighbor:

Limit orderLimit orderLimit order

1 jii nnn1jn

and

Or one may have a new market order that eliminates the order

at the current price and goes to the first neighbor followed by the next limit order

Limit orderLimit orderLimit order

1 jii nnn1jn

and

Else one may have a new market order that eliminates the order at the current

price at the common price and goes to the first neighbor followed by the next limit order

Limit orderLimit orderLimit order

1 jii nnn1jn

and

Mnn2

11

2

1

If one has M limit orders per Market order, the distribution of interval lengths is

A power laws with exponent given by the implicit transcendental equation:

For M~1 one gets ~1.9 consistent with the market data

and not with the continuous approx

0) Social Critical Percolation, Social percolation models Physica A: 277 (1-2) (2000) 239 http://shum.huji.ac.il/~sorin/soc-per.ps GerardSocial Percolators and Self Organized Criticality in Handbook of Graphs and Networks: From the Genome to the Internet, p.113 eds. S. Bornholdt and H. G. Schuster, Wiley-VCH, Berlin, 2002. Anti-Percolation; antivirus ; Parallel Networks (SN); herding (Tom help)

Density of potential adopters: 26 /48 > 50%

Percolation transition

From non-sales at all to a lot of sales

Infinitely sharp at infinite size system

0) Social Critical Percolation, Social percolation models Physica A: 277 (1-2) (2000) 239 http://shum.huji.ac.il/~sorin/soc-per.ps GerardSocial Percolators and Self Organized Criticality in Handbook of Graphs and Networks: From the Genome to the Internet, p.113 eds. S. Bornholdt and H. G. Schuster, Wiley-VCH, Berlin, 2002. Anti-Percolation; antivirus ; Parallel Networks (SN); herding (Tom help)

prob

Effects of

Expectations Adaptation

Self tunning to criticality

Fractal fluctuations

and correlations

ALSO: effects of

Expectations Adaptation

Fractal space-time fluctuationsProduct Success prediction (15/ 17)

Resistance

Resistant

AcceptantAcceptedalready

Acceptant

Resistant

Acceptedalready

Acceptant

Acceptant

Resistant

Acceptedalready

Acceptant

Acceptant blocked

Resistant

Acceptedalready

Acceptant

Acceptant blocked

Resistance

Resistant

Acceptedalready

Acceptant

Acceptant

“ANTI-Percolation”

Antivirus

Parallel Networks

Consumption;

Home

Workplace

Expectations

Consumption;

No herding

Expectations

No herding

+

Consumption+Expectations=Herding

home

work

Consumption;

Home

Workplace

Expectations

home

work

0.1 Testing the Turing Test; Do Men Pass the Humanity Test? International Journal of Modern Physics C (Ruthy; to appear)

3) Can one predict and verify predictions in Economics?Connecting wealth distribution exponent to market returns exponent

Pioneers on a new continent: on physics and economicsQuantitative Finance (IoP) Vol 3, No 1, C12 Feb 2003

2) Stability of Pareto-Zipf law in non-stationary economies in: Economics with heterogeneous interacting agents, ed. A.Kirman and J.B. Zimmermann, Lecture Notes in Economics and Mathematical Systems, Springer, 2001 p 141 http://xxx.lanl.gov/abs/cond-mat/012479 Co-Evolutionist Stochastic Dynamics: Emergence of Power-LawsPower-laws in stochastic Lotka-Volterra-Eigen-Schuster Systems in: "Towards Cognitive Economics", Eds: P. Bourgine and J.-P. Nadal, Springer (2003).

Go To special presentation

4) AB- Model, Emergence of Localized, Adaptive, Resilient objects from Noise, The importance of being discrete: Life always wins on the surface Proc. Natl. Acad. Sci. USA, Vol. 97, Issue 19, 10322-10324, September 12, 2000 http://xxx.lanl.gov/abs/adap-org/9912005

The risk of being unfair, the unstable fate of globalization (2003) Artific Life 4(9) 357

Innovations Refuse to Die:-The Unforeseen Longevity of Society Fundamental Ideas.(2004) Technological forecasting and Social Change In press The Immune self; Emergence of the Body Self-Cognition Proliferation and competition in discrete biological systems. (2003) Bulletin of mathematical biology 65(3) 375-396

Go To special presentation

5) Artificial Creativity Creative Sparks Science 285: 1495-1496, 1999; http://shum.huji.ac.il/~sorin/creative-sparks.htm

Communication at the speed of sound

Herald Tribune

6) Diagonal Link and Novelty EmergenceTemplates of original innovation: Projecting original incremental innovations from intrinsic information (1999) Technological Forecasting and Social Change, May, Vol. 61/1 P. 1-12.

7) What are Stories made of?What Are Stories Made Of? Quantitative Categorical Deconstruction of Creation International Journal of Modern Physics C, Vol. 11, No. 4 (2000) 827-835 http://xxx.lanl.gov/abs/cond-mat/0008192

Figure 2b: General scheme underlying the replacement version of the pictorial analogy template

Symbols set

Symbol 1 Symbol 2 Symbol 3

Product Message

Product space

P1

P2

P3 Matching by a linking operator

?

P4

8) Traces of Mind; Emergence of Meaning in Drawings Emergence of Representation in Drawing: The Relation Between Kinematic and Referential Aspects Cognitive Development 13, 25-51 (1998)

9) Microscopic Seers and the emergence of 3 d visionRestricted Ability to Recover 3D Global Motion from 1 D Motion Signals: Theoretical Observations, Vision Research 35 (1995) 569-578.

10) Complexity Faces the Music. Structures of the Mind and Universal Music Science 2001 June 29; 292: 2433 http://shum.huji.ac.il/~sorin/structures.htm

11) Solving Traffic Jams: Human Intervention or Self-Organization? International Journal of Modern Physics, Vol. 14, No. 8 p 1007

12) Living Tree of knowledge; DiscussionDistrict; Self-mapping, Self-Organization and Dynamical Ontology of Communities

13) Networks and K-cores scaling

14) Genetic vs Internet network;

100

101

103

104

105

106

= -2.99

2) Clusters vs. cores

core #

K~(1+ L/M)

A

BC

DC

A

36546, Z=46

B

253270, Z=23

826, Z=2.83 442, Z=2.22

Surf->linkCopy of gene at other location