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Antwerpen WP5 workshop on Trust, Self-organisation and Complexity Systems

Trust building models and self-organizing systems / complexity theory

author: Margeret Heath, Free University of Brussels
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Slides
0:01 PoSS~ibilities-part01
1:50 PoSS~ibilities-part02
7:09 Picture01
7:31 PoSS~ibilities-part03
12:05 PoSS~ibilities-part04
14:11 PoSS~ibilities-part05
15:43 Picture02
16:41 What form of Complexity?
17:34 Complexity Theory: “… focuses on complex, non-linear, open systems. Complex systems respond to perturbation by self-organizing into emergent forms that cannot be predicted from understanding of its
19:13 PoSS: Measures and Models-part01
20:30 PoSS: Measures and Models-part02
21:41 PoSS: Measures and Models-part03
21:59 PoSS: Measures and Models-part04
22:57 PoSS: Measures and Models-part05
23:57 PoSS~ibilities ….. A PHILOSOPHICAL PAUSE …..
24:12 PoSS~ibilities Mapping Complexity produces 4 classes:
25:12 Mathematical and computational tools for inferring the causal architecture And these are pretty complicated. Tools from Dynamical Systems Theory; Statistical Mechanics, and Algorithmic approaches to
25:30 PoSS # 1: This ‘fractal’ art structure is a beautiful example of how form emerges from ‘order’ parameters of self-organizing systems over time. In this case, someone ‘tweaked’ them (played) and to ou
26:31 PoSS # 2: The FUTURE is dependent on what is what is happening NOW; What is happening NOW is a ‘state’ in a system; NOW is a combination of outside and inside ‘coupling’ This is a SYSTEM
27:39 PoSS # 3: ORGANIZATION is INVARIANT
31:07 PoSS # 4
34:53 PoSS # 5:
36:11 PoSS # 6
37:03 PoSS # 7: GLOBAL scale Ordering
41:13 PoSS # 8
42:07 PoSS # 9
43:59 Picture03
49:18 Aims
52:44 Assumptions about computation in the brain basis of Connectionist. Models-part01
54:23 Assumptions about computation in the brain basis of Connectionist. Models-part02
55:14 Assumptions about computation in the brain basis of Connectionist. Models-part03
56:54 Assumptions about computation in the brain basis of Connectionist. Models-part04
59:59 Assumptions about computation in the brain basis of Connectionist. Models-part05
61:03 Picture04
62:04 Advantages of Connectionism
62:40 Advantages of C.M.-part01
62:52 Advantages of C.M.-part02
63:10 Picture05
64:26 Recurrent Architecture: Flow of Activation
65:00 Flow of Activation
65:18 Communication-part01
65:52 Flow of Activation RE01
66:07 Communication-part01 RE01
66:32 Communication-part02
69:42 Communication-part03
70:34 Communication-part04
70:59 Communication-part05
71:05 Distributed Cognition
71:40 Distributed Cognition the collaboration link?
71:51 Distributed Cognition RE01
72:04 Distributed Cognition the collaboration link? RE01
72:31 Collaboration & C.M.
73:24 Picture06
73:27 Multi-Agent Model: Activation Flow
73:47 Multi-Agent Model: Weight Change-part01
74:17 Multi-Agent Model: Weight Change-part02
74:32 Multi-Agent Model: Weight Change-part03
74:56 Role of trust weights-part01
75:12 Applications
75:29 Role of trust weights-part02
75:36 Maxim of Quantity
75:39 Maxim of Quantity (Novelty) Lyons & Kashima (2003)
76:08 Role of trust weights: Implication
76:29 Picture07
76:31 Hutchins: Getting internal agencies into co-ordination with external structure
77:32 Disturbed cognition
79:58 PoSS~ibilities-part06
81:37 PoSS~ibilities-part07
84:55 PoSS~ibilities-part08

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Reviews and comments:

Comment1 Margeret, October 17, 2007 at 10:31 p.m.:

The original version of this video is unedited, unfortunately, and the technical problems are irritating. I wish that I had been more specific and less nervous at the time, but experience certainly makes one a better presenter. I'd be happy to answer question that folk might have on complexity per se and to offer corrections to erroneous 'suggestions' that might have arisen in this presentation.

The marrying of hard systems with soft-systems is never an easy one (if at all possible); the idea that "trust" as a subjective experience can be captured by parameters of informational interaction, or even simple communicative patterns is naive. It is naive, especially, without the positing of an embodied form of interaction, or some 'grounding' that resides in the physiological parameters/emotional variables that one could use as indications thereof.

One of the things I enjoy most about learning and research is the certainty that one changes one's notions as a result of the activities of research and that with time and care one is able to provide higher resolution ideas to answers given as refutations earlier in one's career.


Comment2 Adkirn, October 22, 2007 at 6:12 p.m.:

Brilliant work, Margeret. Patterning......thank-you for the insight.


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