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 modal 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

These images are reproduced courtesy of The Estate of W. Ross Ashby. Copyright 1972, 2008 © The Estate of W. Ross Ashby

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