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Volume 20 of W. Ross Ashby's Journal
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1956
Volume 20
5343+03 5343+04
Summary: Basic methods with complex systems.
Operational research in silting of rivers
Silting Laws of silting
Adaptation accumulation
Retroactive inhibition condition for zero retroactive inhibition
The Multistable System [108]: Multistability, i.e. separation of learning parts, proved necessary 5345. (Better proof than in Design for a Brain S.17/2)
5344 5345
5346 5347
5348 5349
5350 5351
5352 5353
Diagram of immediate effects (D.I.E.) for accumulation of adaptation
Summary: What can be deduced from the accumulation of adaptations. 5360 Simpler: 5732
5354 5355
Summary: What is necessary for the accumulation of adaptations. 5410, 5540, 5592, 5601, 5617, 5632, 5746
Dispersion proved necessary
Dispersion redundant
Redundancy in dispersion
5356 5357
Summary: Dispersion demands redundancy. 5372, 5379
5358 5359
Summary: A system that attempts to correct multiple arcs will go to an equilibrium with a certain fraction of its arcs correct. If momentarily better than that fraction, it will drift back to it. 5410, 5415
Retroactive inhibition prevented operatively
The Multistable System [109]: A system that adapts by correcting multiple arcs moves to an equilibrial "percentage adapted" - for the more there are adapted, the greater is the chance that correction of one unadapted will upset the adapted, 5360.
Relay can do anything
5360 5361
5362 5363
DAMS Mark II (Dispersive and Multistable System) [5]: Relays can do everything. 5365.
5364 5365
Summary: Relays can do everything I want, if suitably coupled.
Summary: Inputs and outputs of a relay.
5366 5367
Summary: A system of variables each of which does not depend on its past can depend on the system's parts if it contains internal feedback. 5397.7 Example 5412
The Multistable System [110]: How much should discriminative feedback spread? - As wide as the spread of the errors. 5369.
5368 5369
Summary: Discriminative feedback's optimal spread depends on the spread of constraints in the environment.
Discrimination optimal spread
Summary: Feedback in a dispersive system should be first wide-spread and then progressingly narrower. 5413
Discrimination should contract with time
The Multistable System [111]: Destructive feedback may at first, in the history of the multistable system, be scattered widely but should steadily be scattered in narrower range. 5371.
5370 5371
Channel capacity crowding within
Information loss by crowding
5372 5373
Summary: How fast information decays when passed through a number of variables at random. 5381
Summary: If a system is affected, with feedback by another, each can be regarded as a transducer with separated input and output (= conceptual uncoupling). 5428
Feedback conceptual severance
5374 5375
Training importance of
5376 5377
Summary: Environments that have to be adapted to fall into two very different classes: those that do, and those that do not, contain a teacher. 5382.6
Environment with teacher
Arc overlap of
5378 5379
Summary: Keeping things apart by giving them room to spread in is too wasteful. r things would require about r2 spaces.
Dispersion amount of overlap
The Multistable System [112]: Keeping reactions apart by giving them room to spread is costly in material and space. 5380.
5380 5381
Summary: Probability of district balls getting into same cells. 5830
Summary: Abstract form of a "teacher". 5430
Essential variables sequenced by teacher
Training abstract nature of
5382 5383
5384 5385
5386 5387
Arc to shift or not to shift
The Multistable System [113]: If a change of step-mechanism (due to corrective feedback) makes an arc change place, more space is required. If the change makes an arc change nature but not place, more time is required. 5388.
Summary: Time of adaptation can be cut down if more space is available. The distinct reactions should be sent to distinct places, any one reaction should not change its place during its training. 5410, 5415
Habituation and plasticity
Plasticity in system
Reflex, conditioned and plasticity
5388 5389
Clay behaviour of
Summary: "Plastic" behaviour. by itself, specifies nothing about parts or their couplings. [deleted]
Summary: "Having many small basins" does not give any information about parts or couplings.
5390 5391
Diagram of immediate effects (D.I.E.) and length of trajectory
Joining and length of trajectory
Trajectory length and coupling
Feedback and length of trajectory
5392 5393
Summary: Relation between amount of coupling and length of trajectory. 5399, 5411. Summary 5524
Cycle of maximal length
Trajectory size and number of confluants
5394 5395
Plasticity D.I.E. (diagram of immediate effects) for plasticity
Summary: Layout necessary for a plastic transducer, of brief trajectory. 5421, 5476, 5522, 5631
5396 5397
Summary: Multiple equilibria, in the systems in a chain, give a transducer with memory.
Equilibrium in a chain of systems
Transducer with memory but no feedback
Rubin and Sitgreaves' set of transformations
Transducer random, and model trajectory
5398 5399
Summary: Another approach again suggests that trajectories get very long if system gets large. 5407.5, 5479 Summary 5524
5400 5401
Equilibrium in parts and whole
Equilibrium parts with one equilibrium only
Part equilibrium in, and whole
5402 5403
Joining and state of equilibrium
5404 5405
Summary: Equilibria in part, in whole, and coupling. Rich coupling can create equilibria (and destroy them) 5447, 5983. Summary 5524
5406 5407
Equilibrium whole with 50% states equal
Summary: An indefinitely large system with half its states equilibrial, and no trajectory longer than one step. 5471.6, Opposite 5412, 5524
Trajectory short trajectory in infinite system
5408 5409
Arc must be discriminated
Discrimination must be used
Feedback must be discriminative
The Multistable System [115]: A system that accumulates adaptations must use discrimination in its distribution of corrective feedback. 5410.
Summary: A system that accumulates adaptations with appreciable success must use discrimination in its distribution of corrective feedback. 5415, 5421, 5440, 5610
5410 5411
Summary: Some systems with long cycles. No equilibrium 5455
Cycle of maximal length
Trajectory of maximal length
Arc modified later
Feedback to previous arc
5412 5413
Summary: If active arcs have a non-transient trace, feedback can correct that which caused the bad reaction. 5629
Discrimination should be spread to earlier arcs
5414 5415
Accumulation (of adaptations) discrimination necessary
Discrimination must be used
Retroactive inhibition quantative estimate
5416 5417
Summary: If a system accumulates adaptations, it must have some way of getting the disruptive feedback fairly accurately to the appropriate step-mechanisms. 5440, 5606, 5655
5418 5419
Summary: Behaviour may be plastic in two senses: showing an effect or showing a copy. 5437
Plasticity types of
Natural Selection [86]: Genes and arcs of multistable systems regarded as similar, 5421.
The Multistable System [116]: Multistable system and gene-pattern both demand DIAGRAM 5421.
5420 5421
Summary: The system that is both multiple and plastic. 5522, 5545, 5535, 5631
Habituation as by-product
DAMS Mark II (Dispersive and Multistable System) [6]: Design for survival - all else will come. 5422.
Summary: Go for the quality of "survival" - all the rest shall be added unto you.
Iterated systems Wiki
5422 5423
Genes and arcs
Iterated systems Wiki
Summary: Arcs and genes. 5522 (Reprints 130, 131)
Iterated systems Wiki
Reducibility multistable system as adaptive to
Vorticella feeding analogy
5424 5425
Summary: Remember that an input may work by releasing, to the output, some sub-system within: - the jukebox.
Arc may be released
Iterated systems Wiki
Juke box
Iterated systems Wiki
The Conditioned Reflex [46]: Conditioned reflex may use any response that is not too flexible / not too rigid. 5427.
5426 5427
Iterated systems Wiki
Reducibility general meaning
Iterated systems Wiki
5428 5429
Summary: A trajectory may be reducible (into parts that are unconditionally good or bad). 5462, 5532, 5537, 5573, 5675
Accumulation (of adaptations) reducibility implied
Essential variables when reducible
Reducibility of outcome
5430 5431
5432 5433
Constraint reducibility as
Reducibility inplies constraint
5434 5435
Summary: Reducibility in a set of trajectories, 5441, 5528, 5537, 5626
Accumulation (of adaptations) fundamental rule
Iterated systems how much iteration?
The Multistable System [117]: How should the multistable system be didvided? - So that each irreducible "Good" has its own ultrastable system. 5436.
The Multistable System [118]: Fundamental rule for the multistable system: if the major "Good" is to be obtained by the accumulation of minor "goods", then each minor good should have an ultrastable system to itself. 5436.
Experience and learning structure
Plasticity and gaining structure
Structure learning external structure
5436 5437
Summary: "Gaining structure" as "experience to a set of trajectories." 5552
Summary: Demonstrate the state of a system by giving a stimulus to a dominated system and see its trajectory. 5552
Demonstration of state by trajectory
State observation by trajectory
Trajectory as representing state
5438 5439
Summary: Farley demonstrates a statistical machine that adapts.
Discrimination in Farley's machine
5440 5441
1957
Joining and generality
State representation by
Transformation most general form
Variable do not add generality
5442 5443
Summary: The transformation on unanalysed states is completely general provided that... 5456, 5474, 5466
Summary: Constraints on parts and couplings show in the transformation on states. 5456, 5460 5466, 5474, 5524
5444 5445
Summary: Anti-habituation may occur. 5490
Habituation is not necessary
Equilibrium probability of
Joining and probability of equilibruim
Part and probability of equilibrium
Probability of equilibrium
Sample space probability of equilibrium
5446 5447
Joining fully general
5448 5449
Summary: If all parts have a constant probability that a given state, for various conditions, is equilibrial*, the whole's probability that its (whole) state is equilibrial depends on the coupling. 5461 * And one arbitrary, coupling is used.
Joining for many equilibria
5450 5451
Summary: If all the parts have probability π of being in equilibrium, the whole's probability may be as high as π. (For this to happen, the coupling must be highly selected, for each part must, as it were, both give and take equilibrium without loss) 6019
5452 5453
Summary: If parts have most of their states equilibrial, and are many, the whole may [for a suitably selected coupling] have remarkably few equilibrial states; maybe none at all if π ≤ 1-(1/n). 5670, 5484, 5489. Summary 5524
5454 5455
Joining 'random'
Random coupling
Iterated systems "coupling" of
5456 5457
Summary: Meaning of "coupling at random", so as to get a sample space. 5474, 5481.7, 5500. Summary 5524
Transition probability with random coupling
5458 5459
Summary: If each variable goes equiprobably to its next value, and the couplings are equiprobable, then the transformations of the whole make each state of the whole go equiprobably to all states. The equiprobability does not follow if either variables' transformations or couplings are not equiprobable. [deleted]
5460 5461
Cycle commom in random transformation
Equilibrium rare in equiprobable transformation
Rubin and Sitgreaves' set of transformations all trajectories end in cycles
Equilibrium can be made dense
5462 5463
Summary: Equilibria must be specially fostered; in the general random system they are vanishingly few. 5476, 5482, 5503. Summary 5524
Summary: A game for the machine.
Games for DAMS (Dispersive and Multistable System)
DAMS Mark II (Dispersive and Multistable System) [8]: How to invent a game for DAMS II - let it show what it is good at. 5465.
5464 5465
Transition probability building for equality of
5466 5467
5468 5469
Summary: What sort of parts, how coupled, give the whole in which all transitions occur in all combinations? 5474, 5489, 5662, 5982. Summary 5524
5470 5471
Summary: A system as large as you please, with no trajectory exceeding three steps.
Summary: Mean length of trajectory when system has high probability of finding the next state equilibrial. 5479, 5504
Trajectory mean length
5472 5473
Joining fully general
Organisation full generality
Summary: How the building of any whole from parts can be given complete generality: let each part's input range over all other part's states; and let the cells of the table be filled arbitrarily and independently. 5482, 5507, 5662
5474 5475
Design for many equilibria
Equilibrium design for many equilibria
DAMS Mark II (Dispersive and Multistable System) [9]: Design for many equations 5476.
5476 5477
Summary: That a whole should have many states of equilibrium, given that designs of parts are not to be matched to parts, it is necessary and sufficient that each part have many states of equilirium. Summary 5524, 5489
Summary: Making a whole of parts each with a high probability of equilibrium is sufficient to ensure short average length of trajectory (but not necessary). Example 5408
5478 5479
Summary: The world that is is just those properties that are not relative to the observer.
Experimenter and the "real" world
Reality meaning of
Summary: Page 5407 clarified.
5480 5481
5482 5483
Summary: If the parts have probability of equilibrium πi, and if the parts have all combinations of canonical representation, and if all cells in the same representation are filled independently, then the probability of a state of the whole being equilibrial is Πiπi. If joined so that all information is brought to each part, the probabilities are independent. 5505
5484 5485
Summary: If the parts have probability of πi of being in equilibrium, and if the parts vary fully in their canonical representation but the coupling are restricted, then the probabilities of two or more states being in equilibrium (in the whole) are no longer independent. Summary 5524
5486 5487
Summary: "Probability of equilibrium" summarised. [deleted]
5488 5489
Summary: Habituation.
Accumulation (of adaptations) rate of
Equilibrium rate of accumulation
Habituation rate of accumulation
5490 5491
Summary: Synthetic habituation.(Continued 5494.6)
5492 5493
Summary: Repeated samples with some sticking.
Summary: Synthetic display of habituation and its "inhibition".
De-habituation
Inhibition of habituation
5494 5495
5495+01 5495+02
Summary: The use of a transformation repetitively in time is a constraint, so structure becomes apparent.
Constraint and structure
Structure in determinate machinery
Basin meaning changed
Confluant (takes over from "basin")
Confluant defined
Machine random
Random machinery
5496 5497
Summary: "Confluent" defined (as noun). 5512
Machine Markovian
Markov process / chain in machine
Summary: The theory of the determinate machine includes the practical aspects of the theory of the Markovian machine.
Joining 'random'
Random coupling
5498 5499
5500 5501
Summary: Sample space of a whole made from parts by coupling, they having sample spaces of their own.
Confluant number of, and reducibility
Reducibility and number of confluants
Summary: One system may have many confluants, and many separated systems may have a single confluent
5502 5503
Equilibrium probability of
Trajectory random
Transition probability in machine of parts
5504 5505
Summary: The whole built from random parts, by random coupling, when each part has probability πi that its state is equilibrial, does not go (if not in equilibrium) equiprobably to all states but favours those "near" itself. Summary 5524
Metric Hockett's metric
Summary: Refusal to give a machine (or state, or input-valve, or transformation, etc) a particular value corresponds to talking about a set of machines (or states, or input-values, or transformations, etc). The set has no associated probabilities, but can use the concept of "independence". 5666.7
Equilibrium probability of
Random machinery
Rubin and Sitgreaves' set of transformations is fully unspecified
Set or Ensemble and lack of specification
Specification lack of, and set
5506 5507
Axiom of No Design
Constraint total absence
Design total absence
5508 5509
Summary: The system that is contained only to have high equilibrium in its parts.
Reducibility by equilibria in parts
Summary: High probability of equilibrium in the parts cuts the whole up into (temporarily) isolated sub-systems. 5522
5510 5511
Habituation fundamental theorems
5512 5513
5514 5515
Axiom of No Design
5516 5517
Hover mouse here to display note
5518 5520
5519 5519+01
Threshold and habituation
Hover mouse here to display note
5520+01 5521
Summary: Habituation and its relation to equilibrium.
Arc arcs, must be in sheet
Summary: The system that habituates must be a flat sheet. (But see 5632) 5545, 5631
Summary: of relations between equilibria in part and equilibria in whole. 5259 (See article for refs) 5317, 5510
Cortex must be a sheet
Equilibrium reviewed
Equilibrium anatomy of cortex
5522 5523
Equilibrium reviewed
Equilibrium reviewed
Rubin and Sitgreaves' set of transformations probability of equilibrium
5524 5525
Equilibrium reviewed
Summary: Relations between equilibria in parts and equilibria in whole collected from the last 130 pages. Review 5983 5667, 6019, 6025, 5436
Equilibrium reviewed
5526 5527
Reducibility in essential variables
5528 5529
Summary: Reducing major Good to minor goods. 5537, 5532, 5578, 5626
Essential variables when reducible
Introduction to Cybernetics reviews
Personal notes [31]: Reviews of the "Introduction to Cybernetics". 5531, 5582, 5630, 5748.
5530 5531
Conditionality in set theory
Organisation in set theory
Organisation as conditionality
Reducibility in set theory
Summary: Basic meanings of organisation, reducibility, conditionality. 5537, 5675, 5993
Isomorphism example in differential equations
5532 5533
Summary: Example of isomorphism in differential equation form.
5534 5534+01
Summary: The time-factor insists that genetic adaptations and cerebral-learned adaptations shall be done mostly in the piece-meal way. 5601, 5631
Time allows only time
5534+02 5535
Summary: Where I am now. 5558
Personal notes [29]: Notes re-read from p. 1000 in Feb '57 5536.
5536 5537
Summary: From essential variables to Grand Outcome, via trials. 5573, 5642
Essential variables and trials
Immediate effect equals "cause"
Trial and error and essential variables
Cause and feedback
Discrimination requires information
Feedback discriminative needs information
Immediate effect and feedback
Requisite Variety, Law of in discriminative feedback
Supplementation in discriminatative feedback
5538 5539
Summary: Feedback cannot be discriminating unless an adequate channel brings the necessary information; (but any particular channel may perhaps be supplementable) 5628.7, 5547, 5584
Order of speed of working
Part of higher order of speed
5540 5541
5542 5543
Summary: Systems with super-fast sub-components.
Arc in sequence
Chess as double process
Thinking as cerebral process
5544 5545
Summary: "Thinking things over" in a multistable system. Discriminative feedback requires mere opportunism. 5549, 5584, 5601
Discrimination requires information
Feedback discriminative needs information
5546 5547
Selection requires information
Summary: No general principle can be sufficient guide when selection must be done; some actual channel is also necessary. 5585
Arc selection of
Essential variables discrimination by
Feedback methods for discrimination
5548 5549
Summary: In all cases so far, all arcs are assumed to have some sign that they are, or have recently been, active, and the discriminative feedback hits only those with the sign. 5557, 5584, 5601, 5609, 5628
Activity as information for feedback
Discrimination methods known
Summary: Unsolved problem. (Strachey's solution, 5559)
Memory is there a minimal quantity?
5550 5551
Experience and learning structure
Structure learning external structure
Diffusion of organisation
Organisation diffusion of
Structure diffusing in
5552 5553
Summary: The "diffusion" of structure is a manifestation of a whole which is really a chain going to equilibrium.
5554 5555
Summary: More on the spread of "structure".
Summary: Others are building machines with discriminative feedback. 5584
SNARK built by Minsky
Activity as information for feedback
Feedback discrimination used by SNARC
Feedback discriminination used by Farley
5556 5557
Summary: Personal note.
Personal notes [30]: Have the Notes come to an end? 5558.
Summary: The optimal duration of memory.
Summary: A minimal quality of memory is not definable.
Constraint and optimal duration of memory
Memory optimal duration
5558 5559
Function random function
Orthogonality of criteria
Pattern (in general) recognition of
Recognition by random functions
5560 5561
5562 5563
5564 5565
Orthogonality of random criteria
Random criteria
5566 5567
Summary: Identification by random criteria is (in the defined circumstances) practically as good as accurate dichotomy.
Summary: Major strategies are determined at the genetic level, minor at the cerebral.
Experience
5568 5569
Summary: How this works yields application to psychiatry. 5651
Psychiatric applications [92]: This work yields applications to psychiatry as by-products. 5570.
Aggression and regulation
Variety in aggression
5570 5571
Summary: The distinction between aggression and non-aggression corresponds, respectively, to having or not having a regulator. 5694
Regulation as aggression
Essential variables abstract form
Machine essential variables of machine
Survival and essential variables, abstractly
5572 5573
Parameter as essential variables
5574 5575
Summary: The "essential variables" to a machine with input are those other parameters to it whose change would alter its canonical representation.
Essential variables to a machine
Machine not equal to 'system'
5576 5577
Summary: "System" and "machine with input" are very different.
Essential variables sub-essential variables found by system
Goal and sub-goal
Part-function and sub-goal
Sub-goal found by system
Summary: Essential variables in Multistable System 5601, 5625, 5642
5578 5579
Control environment as problem in
Environment general abstract form
Puzzle Box as generalised environment
Summary: General formulation of "the environment" for an artificial brain. 5522
5580 5581
Introduction to Cybernetics reviews
The Multistable System [119]: What in the environment are the special characteristics that the multistable system is specially adapted to? 5582.
Personal notes [31]: Reviews of the "Introduction to Cybernetics". 5531, 5582, 5630, 5748.
Feedback discrimination used by MacCallum
Logic MacCallum and Smith's
5582 5583
Summary: Solution in principle of the problem of discriminative feedback. 5590, 5594, 5601, 5608, 5631
Requisite Variety, Law of in discriminative feedback
5584 5585
5586 5587
Summary: Any question about how something can be achieved is answered: a regulator is necessary; lacking it the achievement is impossible. 5601
Adaptation sequential and simultaneous
5588 5589
Summary: Serial or sequential adaptation is equivalent, in a sense, to semi-iterated simultaneous adaptation. 5593
Summary: General phenomena should be explained by proportionately general mechanisms.
Oddments [45]: General phenomena should be explained by proportionately general mechanisms. 5591.
5590 5591
Adaptation accumulation
Arc accumulation of adaptations
Conscious mind dream of the archer
The Multistable System [120]: Accumulation of adaptations 5592.
5592 5593
Summary: What is necessary for the accumulation of adaptations. 5601, 5608
5594 5595
Iterated systems
5596 5597
Part-function does not imply randomness
5598 5599
Summary: From iterated systems to the multistable. 5612
Essential variables when reducible
The Multistable System [121]: Newer theory of multistable system. 5601 et seq.
5600 5601
5602 5603
Speed (of adaptation)
Summary: What is necessary for fast adaptation by reducibility. Much modified 5608 5736
5604 5605
Dispersion random dispersion useless
Reducibility finding, while adapting
Trial and error must not change dispersion
Summary: Random dispersion will not achieve a useful degree of reducibility. 5619
5606 5607
Discrimination methods known
Feedback discrimination used by MacCallum
5608 5609
Disturbance reducible
5610 5611
Adaptation adaptation is to a set of disturbances
Disturbance as the ultimate enemy
Summary: When the set of disturbances is a product set of minor disturbances, each of which has its appropriate reaction unconditionally, accumulation is adaptation is readily obtained. Often, the set of disturbances must be defined explicitly.
5612 5613
Summary: There are two quite different "lengths of trajectory." Better "transient"
Speed (of adaptation) definition
Trajectory length, in adaptation
5614 5615
Essential variables when reducible
5616 5617
Summary: Conservation (or accumulation) of adaptations as deference against imperfect isolation, when the "leakage" occurs in slow discrete steps. 5620, 5746
Disturbance occasional repetitive
Isolation imperfect
The Multistable System [122]: The multistable system is the natural specialisation to the disturbance that comes rarely but repetitively. 5618.
The Multistable System [123]: (Brief review of position) 5619.
5618 5619
Summary: The multistable system re-viewed. 5733, 5735, 5746
The Multistable System [124]: I now (1957) regarded as a special case in a more general formulation. 5621.5.
5620 5621
Arc optimal size
Brain why large?
5622 5623
Summary: How big should an arc be? 5746
Arc why dynamic?
5624 5625
Summary: Why have arcs that are dynamic systems?
Essential variables set theory
5626 5627
Summary: Reducibility of the essential variables in set theory. 5631, 5642, 5652, 5675
Reducibility in essential variables
Summary: How good a synthetic brain can I make?
Discrimination should be spread to earlier arcs
DAMS Mark II (Dispersive and Multistable System) [10]: My artificial brain must concentrate on selection. 5629.
5628 5629
Introduction to Cybernetics reviews
Personal notes [31]: Reviews of the "Introduction to Cybernetics". 5531, 5582, 5630, 5748.
Summary: The principles of search are not altered if what we search for is a decision (about what to search for - at a lower level)
5630 5631
Arc bounds of
5632 5633
Summary: One unit for adaptation (in Multistable System) may comprise many portions (arcs) in the cortex. 5653, 5746
The Multistable System [125]: One unit for adaptation (one "arc") may comprise many portions of both cortex and environment. 5634.3.
Summary: Optimal duration of trial; optimal time back to make disruptive feedback work. 5642
Essential variables maximal speed
Trial and error maximal speed
5634 5635
Summary: Continuity as a restraint.
Constraint continuity as
Continuity as constraint
Trial and error duration of
5636 5637
5638 5639
Summary: The natural duration of a trial is the time of transmission of information from step-mechanism round then organism and environment back to step mechanism What is implied by "trail."
5640 5641
Essential variables vital variables
Survival and vital variables
Vital variables defined
Summary: Distinguish between Essential and Vital variables.
5642 5643
5644 5645
Essential variables within random machine
Vital variables in random system
5646 5647
Pay-off in survival
5648 5649
Summary: Vital variable identified generally; what it is vital to; sub-goals. 5811
Senility effect of
Psychiatric applications [93]: Review of the points at which applications to psychiatry can occur. 5651.
5650 5651
5652 5653
Arc ways of failing
5654 5655
Summary: Various ways in which senility may affect the primary function of adaptation.
5656 5657
5658 5659
Summary: The information given by the behaviour of a whole, may often be insufficient for unique characterisation of its parts or couplings. 5983
5660 5661
Organisation deducing organisation
5662 5663
Summary: In the relating of properties of the whole to those of the parts, one case (described) is of central importance.
5664 5665
Summary: The unspecified machine.
Machine the fully general machine
5666 5667
Equilibrium reviewed
5668 5669
Summary: The extreme cases of the relations between equilibria in parts and whole. 5983, 6025, 6019
5670 5671
Summary: If the stimuli are not restricted, the terminal responses to Limn→∞TnD mark out the areas of the T- confluants.
5672 5673
Summary: Clearer statements of the theorem on habituation. 5687, 5702.4, 5707, 5730, 6088
Habituation fundamental theorems
5674 5675
Summary: If variables can't communicate, any operator on them may have to be reducible.
Summary: When two operators act alternately they still each have power of veto over any proposed state of equilibrium. 5708
Equilibrium under two operators
5676 5677
Activity spread over net, or decay
5678 5679
Summary: High equilibrium in the parts versus communication of activity between them.
5680 5681
Intelligence as selection
5682 5683
Ancillary regulations finding extrapolation function
Constraint finding
Extrapolation
Future prediction of
Summary: The machine that jumps directly to the answer, by spotting a constraint, extrapolates. It can do this only after having had previous experience with other problems in the same class, and by having a regulator that selects the better extrapolation functions. 5728
5684 5685
Summary: Complexities in integration and coordination may be shown adequately by some simple evidence of their success.
DAMS Mark II (Dispersive and Multistable System) [11]: How it can show its cleverness, 5686.
5686 5687
Computing machines program for habituation
Program (of computer) for habituation
Summary: Program for habituation. 6088
Summary: Normal behaviour is loopy.
5688 5689
Computing machines Progam for ultrastability
Program (of computer) for ultrastability
5690 5691
Summary: The homeostat programmed.
Summary: The dynamic cannot claim that the static is just a sub-case of it.
Dynamic system not more general than static
Static not less general than the dynamic
Summary: Design for a Brain seems to have been successful.
Personal notes [32]: Design for a Brain seems to have overwhelmed the opposition. 5693.
5692 5693
5693+01 5693+02

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