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Trust building models and self-organizing systems / complexity theory
Published on Feb 25, 200710166 Views
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Chapter list
PoSS~ibilities-part0100:01
PoSS~ibilities-part0201:50
Picture0107:09
PoSS~ibilities-part0307:31
PoSS~ibilities-part0412:05
PoSS~ibilities-part0514:11
Picture0215:43
What form of Complexity?16:41
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 17:34
PoSS: Measures and Models-part0119:13
PoSS: Measures and Models-part0220:30
PoSS: Measures and Models-part0321:41
PoSS: Measures and Models-part0421:59
PoSS: Measures and Models-part0522:57
PoSS~ibilities ….. A PHILOSOPHICAL PAUSE ….. 23:57
PoSS~ibilities Mapping Complexity produces 4 classes:24:12
Mathematical and computational tools for inferring the causal architecture And these are pretty complicated. Tools from Dynamical Systems Theory; Statistical Mechanics, and Algorithmic approaches to25:12
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 ou25:30
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 SYSTEM26:31
PoSS # 3: ORGANIZATION is INVARIANT27:39
PoSS # 431:07
PoSS # 5: 34:53
PoSS # 636:11
PoSS # 7: GLOBAL scale Ordering37:03
PoSS # 841:13
PoSS # 942:07
Picture0343:59
Aims49:18
Assumptions about computation in the brain basis of Connectionist. Models-part0152:44
Assumptions about computation in the brain basis of Connectionist. Models-part0254:23
Assumptions about computation in the brain basis of Connectionist. Models-part0355:14
Assumptions about computation in the brain basis of Connectionist. Models-part0456:54
Assumptions about computation in the brain basis of Connectionist. Models-part0559:59
Picture0401:01:03
Advantages of Connectionism01:02:04
Advantages of C.M.-part0101:02:40
Advantages of C.M.-part0201:02:52
Picture0501:03:10
Recurrent Architecture: Flow of Activation01:04:26
Flow of Activation01:05:00
Communication-part0101:05:18
Flow of Activation RE0101:05:52
Communication-part01 RE0101:06:07
Communication-part0201:06:32
Communication-part0301:09:42
Communication-part0401:10:34
Communication-part0501:10:59
Distributed Cognition01:11:05
Distributed Cognition the collaboration link?01:11:40
Distributed Cognition RE0101:11:51
Distributed Cognition the collaboration link? RE0101:12:04
Collaboration & C.M.01:12:31
Picture0601:13:24
Multi-Agent Model: Activation Flow01:13:27
Multi-Agent Model: Weight Change-part0101:13:47
Multi-Agent Model: Weight Change-part0201:14:17
Multi-Agent Model: Weight Change-part0301:14:32
Role of trust weights-part0101:14:56
Applications01:15:12
Role of trust weights-part0201:15:29
Maxim of Quantity01:15:36
Maxim of Quantity (Novelty) Lyons & Kashima (2003)01:15:39
Role of trust weights: Implication01:16:08
Picture0701:16:29
Hutchins: Getting internal agencies into co-ordination with external structure01:16:31
Disturbed cognition01:17:32
PoSS~ibilities-part0601:19:58
PoSS~ibilities-part0701:21:37
PoSS~ibilities-part0801:24:55