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Volume 19 of W. Ross Ashby's Journal
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1954
Volume 19
4993+03 4993+04
Summary: Algebraic form of "immediate effect".
Summary: How to deduce the connexions from input to variable. 5055
Diagram of immediate effects (D.I.E.) and parameters
Input deducing connexions
4994 4995
Summary: "Connexion" depends on the operations brought to its study.
Connexion meaning of
Diagram of immediate effects (D.I.E.) deducing
4996 4997
Isomorphism electromechanical example
Higher geometry of fields and matrix theory [17]: An electromechanical analogy (spring and mass / condenser etc) in detail 4998.
Summary: An exact electromechanical analogy.
4998 4999
Summary: Isomorphism.
Isomorphism formal definition
Machine isomorphism defined
Summary: Homomorphism.
Homomorphism example
5000 5001
Summary: A problem.
Constraint machine as
Machine as constraint
Epistemology [48]: Deducing the machine from the behaviour 5003.
5002 5003
Summary: What is a machine? 5056
Summary: Game that is wholly arbitrary. 5024
Continuity in games
Games wholly arbitrary
5004 5005
Design of reducible machine
Reducibility and design
Joining design in
5006 5007
5008 5009
Summary: Design of a machine part by part. 5474, 5072
Triunique example
Summary: Example of triunique relation.
Feedback bit by bit
5010 5011
Summary: Behaviour when the feedback can carry only one bit.
Regulation all types collected
5012 5013
5014 5015
5016 5017
5018 5019
Summary: The relations between regulators are complex and hardly worth developing.
5020 5021
Problems solving problems
Solution (to a problem) finding
Summary: Problems that are not wholly new. 5066
Summary: A numerical illustration of continuity as a constant. 4569 5005 4597
Constraint continuity as
Continuity as constraint
5022 5023
Summary: Example of the effect of continuity as a constraint. Caution: See 5054. 5636
Diagram of immediate effects (D.I.E.) and memory
Isomorphism in memory
Memory isomporphism in
5024 5025
Summary: Effects of channel capacity in joining two systems, only one of which is observed.
Epistemology [49]: As the coupling between B and A is made richer, either by increasing channel capacity or by adding immediate effects, so will what is in B affect x the sooner. 5026. DIAGRAM
Entropy during search
Hunt and stick information flow
Information during hunt and stick
Searching information flow
Selection informatiom flow
Trial and error gives information
5026 5027
J - function (Ashby) blemish
5028 5029
5030 5031
5032 5033
5034 5035
5036 5037
Summary: Flow of information during trials.
Turing machine principle
5038 5039
5040 5041
Summary: The Turing machine.
Machine reproduction of
Reproduction machines for
5042 5043
Summary: A machine that makes itself. 5088
5044 5045
Hunt and stick in logic machine
Logic machine
Strategy of trial and error
Veto in equilibria
Veto use by McCallum
Summary: McCallum and Smith also use the method of veto. 5583
Requisite Variety, Law of in set theory
5046 5047
Summary: Requisite variety stated algebraically. 5075
Isomorphism in memory
Memory isomporphism in
5048 5049
Summary: The field, when memory is used, is not isomorphic with that found when all is observed.
Epistemology [50]: If only components in J are observable, and we know that the J-states have been, in succession, a0,a1, ... ,ak, and if the machine's mapping is Σ, then the machine must now be in one of the states in EXPRESSION. 5050.
Trajectory deducing others
Higher geometry of fields and matrix theory [6]: Knowledge of one form EXPRESSION for all values of 1...xºn;t is sufficient to define all the others. 5051.
5050 5051
5052 5053
1955
Summary: Studying a system via one variable.
Continuity in discrete sets
Epistemology [51]: The whole system can be studied if one variable is observable; in particular, all the canonical equations can be deduced 5054.
Summary: (Comment on "continuity")
Input found by testing
5054 5055
Summary: Studying a system...
Constraint machine as
Machine as constraint
Protocol deducing input
Summary: "Machine" as constraint in a sequence. But see 5074
5056 5057
Absolute system algebraic test
Canonical equations as [TPT-1]
Canonical equations in set theory
Operator from protocol
Protocol deducing absolute system
5058 5059
Summary: Converting observed behaviour to specification of machine. 5063, 5081, 6071
Summary: Beware! The "design" of a machine costs simply what is necessary to get it selected from what is available. There is no unique quantity "in" a machine. 5006
Design amount in machine
5060 5061
Summary: The quatity of design in measured by the size of the set that is drawn from. 5070, 5071, 5072
Behaviour operations with
Operator for behaviour
5062 5063
Summary: Algebra can operate directly with observed behaviour.
Everywhere defined mnemonic for
Single-valued mnenomic for
Summary: Mnemonic for "everywhere defined" and "single valued".
Summary: Metron and logon.
Logon defined
Metron defined
5064 5065
Summary: What is problem solving? I say it is finding an element in a set.
Problems solving problems
Solution (to a problem) finding
Strategy of problem solving
5066 5067
Summary: Problem solving.
Markov process / chain as problem solver
Summary: Another example of a self-locking system, this one harmful.
Chain on wheel, as self locking system
Self-locking system example of chain on wheel
5068 5069
Deputy design necessary
Design amount for deputy
Machine amount of design
Summary: Briefing a deputy calls for the same capacity as doing the job oneself. 5073
Summary: Amount of design required for a machine to do a job.
5070 5071
Machine amount of design
Summary: More on "the amount of design in a machine".
Amplifier of regulation
Regulation amplification of
5072 5073
Summary: Why build a regulator?
Machine has two aspects
Summary: A machine embodies a transformation and, in addition, may act repetitively.
Summary: Two problems.
Homeostat theory of
Unsolved problems [16]: Represent this by a pay-off matrix:- the case when the disturbance is compound and one component varies only occasionally. 5075.
Unsolved problems [17]: State the thesis that "selection forces adaptation" in terms of disturbance and regulation. 5075.
5074 5075
Summary: Theory of the homeostat.
Amplifier demonstration
Magnet in selection-amplifier
Selection demonstration
Summary: Demonstration of selection-amplifier.
Prediction falsifies itself
5076 5077
Interaction and prediction
Joining and prediction
5078 5079
Summary: Systems that interact finitely with their observer.
Machine as constraint
Machine algebraic in protocol
5080 5081
Summary: The structure of a machine, derived from a protocol.
Protocol deducing machine
5082 5083
Summary: Structure of machine in a protocol. 5170, 5192, 6071
Equivalence relation over protocol
Homomorphism over protocol
Protocol equivalent relations over
Summary: The problem of "simplifying" a machine.
Gödel's theorem described
Simplicity in homomorphisms
5084 5085
5086 5087
Summary: Godel's theorem as process.
Virus as self-reproducer
Summary: More on the self-reproducing system. 5261
Games and constraint
Reproduction example (artificial)
Strategy must fit constraints
5088 5089
Metric and convergence
Summary: A strategy must be related to the actual constraints of a system.
5090 5091
Capacity independent of reducibility
Reducibility independent of channel capacity
Summary: Reducibility and channel capacity are independent. 5532
Linkage
5092 5093
Summary: Finding a maximising formula.
Max( ) (function) strategy of
Joining tensor method
Tensor coupling, re-stated
5094 5095
5096 5097
Algebra of coupled systems
Summary: Formally stated method of coupling by using the tensor product of Riguet.
5098 5099
5100 5101
5102 5103
Summary: Tensor method of coupling systems.
Summary: Tensor method of coupling systems.
Absolute system examples, list of
5104 5105
Latent roots list of
Matrix list of special matrices
5106 5107
Summary: List of shorthand symbols that may be found between pages 4416 and 4446, and in the Index.
Shorthand list of symbols
Personal notes [22]: I start shorthand, 4416, I stop it, 4446, List of symbols, 5108.
Summary: Review of Pringle.
Communication involves set of acts
Evolution Pringle on
5108 5109
Entropy and organisation, in cream
Organisation and entropy
Summary: The problem of the glass of milk.
5110 5111
Summary: What is meant by "He does not know......."
Knowing and size of set
Epistemology [53]: "A does not know B's phone number" means, operationally, that if A is forced to make an attempt at calling, his action must be deternmined by some other, random, factor 5112.
Summary: With systems in general, do not look for the law; each must be studied and taken as it is found. Over a set of systems a constraint may be found. 5114.7.
Society [64]: Societies far from the atomic level are too many to give a necessary law, though a constraint may be found in practice. 5113, 5115.
5112 5113
Summary: Bridgman on operations.
Atom redundancy among atoms
Operational principle Bridgman on
Redundancy at atomic level
Quotations [6]: What a man means by a term is to be found by observing what he does with it, not by what he says about it. Bridgeman 5114.
Society [64]: Societies far from the atomic level are too many to give a necessary law, though a constraint may be found in practice. 5113, 5115.
DAMS (Dispersive and Multistable System) [95]: The "law" of a system (or set of systems) far from the atomic level can be found only empirically. 5115.
5114 5115
Summary: There is no "law" to be found in systems much removed from the atomic level. 5142
Laws of nature only near atomic level
Summary: On causality. (Continued over)
Black box, problem of the "cause" and "why"
Cause Rapoport on
Information statistics as reducer
Large system and statistics
Operational principle "why?" and
Statistic as diminisher of information
Why ...? meaning of
5116 5117
Cause Rapoport on
Operational principle Rapaport on
Why ...? meaning of
Immediate effect equals "cause"
5118 5119
5120 5121
Input and "cause"
5122 5123
Correlation and 'cause'
Memory as "cause"
5124 5125
Goal as "cause"
Teleology as "cause"
5126 5127
Constraint as "cause"
Summary: Concepts of cause, why, because etc related to Black Box theory.
5128 5129
Channel capacity channels and lattice
Diagram of immediate effects (D.I.E.) various, and lattice
Lattice of diagrams of immediate effects
Summary: The simplifications obtained by cutting channels lie on a lattice. 5135
Reducibility in organisation
5130 5131
Organisation advantage of
Design and reducibility
Regulation and reducibility
5132 5133
Summary: Why the organised and inter-connected can usually defeat the unorganised and individualistic.
Channel capacity channels and lattice
5134 5135
Summary: Quantity of organisation.
Network growing instability
Society [65]: Each unit, to improve its own regulation, improves its own channels of communication. But this adds richness to the channels in the whole system, so the whole moves on to a long and complex trajectory, till it hits a critical state. 5137.
5136 5137
Absolute system in history
Disintegration of society
England as absolute system
Independence of England
Isolation of England
Beginning "natural"
Initial state "natural"
5138 5139
Impulse as "starter"
Stimulus as "starter"
History laws of
Laws of nature in history
5140 5141
Society [66]: Toynbee's "laws" of societies 5142.
5142 5143
Summary: Application of system theory to History.
Equilibrium giving binary relation
Machine binary relation in
Relation binary, in machine
Set or Ensemble operations and machine
5144 5145
Summary: How can a machine express a binary relation? 5181
Summary: Law of Experience algebraically. 5155, 5209.7
Experience in algebra
5146 5147
Equivalence relation over times
Simplicity by fusing times
Time equivalence relation time
5148 5149
5150 5151
Summary: Simplification by running together, or deleting, the elements of time. 5165, 5245
Summary: "Loss of control" in set theory. 5155
Control in set theory
Convergence (of lines of behaviour) loss of control
Derivative and set theory
Information non-transmission
5152 5153
Summary: The conditioned reflex, and shedding of scatter by going to an equilibrium. 5249.1, 5277.8
Equilibrium as noise-destroyer
Noise method for destroying
Experience rigorous form
Input forcing convergence
5154 5155
5156 5157
Summary: Law of Experience, given rigorously. 5179
Definition as transformation
Mathematics nature of
5158 5159
Summary: Kershner and Wilcox' book.
Canonical equations information in
Information in canonical equation
Input of mathematical form
Mathematics variety in
Variety in canonical representation
5160 5161
5162 5163
Summary: Variety in mathematical forms. (Continued 5167.6)
Variety shown by family
Equivalence relation on Markov chain
Lattice of Markov simplifications
Markov process / chain equivalence relation on
5164 5165
Summary: Markovian machines simplify on to a lattice.
Summary: Dichotomy versus trichotomy.
Dichotomy is best
Searching dichotomy is best
5166 5167
Input of mathematical form
Transducer mathematical expression as transducer
Summary: Mathematical expressions have inputs and outputs.
Summary: Black Box looks at itself and others.
The subjective [4]: Can inter-personal relations be translated into Black Box terms? Question asked by Urie Bronfenbrenner, 5169.
5168 5169
Operator "spreading" operator
Spreading operator defined
5170 5171
Dependence better
Immediate effect algebraic definition
5172 5173
Summary: Algebraic form of "immediate effect". 6070
Integral equation and my methods
5174 5175
History and integral equation
Memory and integral equation
Summary: The use and limitations of the integral equation. 5192, 5210, 6036
5176 5177
Summary: Must a person's private "map" be observable to all?
Decay of memory
Experience corollary
Memory law of experience
5178 5179
Summary: Memory must fail if new information is forced in. 5205
Machine binary relation in
Relation binary, in machine
5180 5181
5182 5183
Summary: Machine with input and binary relation.
Isomorphism and prediction
Prediction why important
5184 5185
Summary: "A can predict the behaviour of B" is equivalent to "A is isomorphic with B". 5193
Cause Mach on cause
Protocol constraint in
Constraint science as constraint, Mach on
Laws of nature as constraint
Science as constraint
Quotations [5]: Scientific law as a re-coding: "Science itself, therefore, may be regarded as a minimal problem, consisting of the completest possible presentment of facts with the least possible expenditive of thought [his italics]." Ernest Mach 5187.9.
5186 5187
Summary: Quotations from Mach.
Corespondence as constraint
Quotations [57]: "All science has its origin in the needs of life." Ernst Mach 5188.
Summary: The concept of "constraint" includes correspondence, mapping, relation, as special cases.
Constraint correspondence as
Relation as constraint
5188 5189
Summary: Psychological and anatomical patterns will usually be different. Cf. Introduction to Cybernetics S.6/11
Diagram of immediate effects (D.I.E.) anatomical or physiological?
Summary: Two meanings of "input".
Input two meanings
Protocol general theory of
5190 5191
Constraint in protocal, theory
Protocol general theory of
Protocol general theory of
5192 5193
5193+01 5193+02
Canonical equations in protocol
Machine in protocol
Protocol general theory of
Summary: Constraints in protocols. 5978
Protocol general theory of
5194 5195
Protocol general theory of
Protocol general theory of
5196 5197
Memory in protocol
Protocol general theory of
Protocol general theory of
5198 5199
Protocol general theory of
Protocol general theory of
5200 5201
Derivative replacing variable
Difference replacing variable
Protocol general theory of
Protocol general theory of
5202 5203
Protocol general theory of
5204 5204-A
Protocol general theory of
Unobservables replacement by other observations
Protocol general theory of
5205 5206
Protocol general theory of
Protocol general theory of
5207 5208
Summary: Use of observations at times earlier than "immediately preceding." Qualified 5210.3 5228, 5236
Definition and experience
Experience and definition
Protocol general theory of
Summary: Definition, and the law of experience. 5254
Protocol general theory of
5209 5210
Protocol general theory of
Protocol general theory of
5211 5212
Summary: In the absolute system, the use of earlier states may be inefficient. 5869
Protocol general theory of
5213 5214
5215 5216
Summary: Thoughts provoked by Savage.
Summary: The mapping of the homomorphic machine.
Homomorphism [=?µ?-1]
Mapping in homomorphic form
5217 5218
Summary: The structure of the regulator. (Note that the inverse, [w-1], has appeared at last!)
Regulation as inverse
Transducer regulator as inverse
Extrapolation
Future prediction of
Prediction is it possible?
5220 5221
Summary: Must a constraint go on holiday in the future? 5273
Message depends on set
5222 5223
Summary: Example of message that depends on the set it came from. 6275
Step-mechanism ? necessary
Ultrastability without step-mechanisms
5224 5225
Summary: Ultrastability in Design and in Introduction reconciled.
5226 5227
Variety real form of
Summary: Real existence of "variety".
Metastability meaning of
5228 5229
Summary: Metastability.
Metric Hockett's metric
Metric on n-tuples
N-tuple metric difference
5230 5231
Input metric in
5232 5233
Summary: Concept of the "distance" between two input states, or two designs. 5506, 6282
Summary: Distance of movement.
5234 5235
Action at a distance
Distance action at a distance
Noise and action at distance
5236 5237
5238 5239
Summary: Why the scientist should relate the event to what is adjacant rather than distant.
Summary: "Complexity" is a relation between units and construct.
Complexity measure of
Pre-fabrication in complexity
5240 5241
Entropy zero entropy
Homeostasis as noise-correction
Noise homeostasis as anti-noise
Requisite Variety, Law of as noise-correction
Summary: Law of Requisite Variety as law for suppression of noise.
Feedback and persistance
Quantum theory and Black Box
5242 5243
1956
Summary: A minute crack at the problem of consciousness. 5275
Conscious mind and feedback
Self-awareness and persistance
Summary: The end of the hunt?
5244 5245
Equilibrium homomorphism of
Homomorphism of states of equilibrium
Order of time
Summary: The machine, when observed only so far as the states of equilibrium it goes to. 5556
5246 5247
Summary: What is a "variable"?
Variable nature of
Summary: Mathematical proof "in detail" means going through a sequence of states of equilibrium.
Computing machines as noise-destroyer
Digital computer as noise-shedder
Equilibrium as noise-destroyer
Mathematics what is a proof?
Proof nature of
5248 5249
Summary: Is there any way by which a person can communicate an infinite amount of information?
Consistency in maths
Mathematics consistency in
5250 5251
Summary: "Consistency" in mathematics.
Personal notes [24]: My ambition 5252.
Summary: Personal note.
Inference nature of
5252 5253
Summary: What is a "logical definition"?
Deduction nature of
Definition and experience
Infant learning structure
Learning without essential variables
Structure in world
5254 5255
Summary: The structures of space as habituation. 5289, 5313
Habituation to constraint
Space-time structure in
Unsolved problems [18]: What can be said of habituation, or of the events in experience, when the set of vectors shows constraint? 5256.
Basin model with lots
Habituation model for
5256 5257
Reflex, conditioned machine for
5258 5259
Summary: New machine to demonstrate statistical mechanisms. 5317, 5408, 5526
Imitation mechanistic
Summary: On "imitation".
Reproduction more examples
5260 5261
Summary: More "self-reproducing" systems. 5797
Learning in childhood
Pain teaches in youth
Summary: Pain educates mostly in childhood.
Basin distribution of size
5262 5263
Summary: A contribution to the theory of the distribution of basin size.
5264 5265
Basin distribution of size
Summary: Probability of getting a single basin. 5308
Model Rosenblueth and Wiener
5266 5267
Schizophrenia loss of constraint
Psychiatric applications [68]: Is schizophrenia characterised by increasing noisiness? 5268.
5268 5269
Summary: Schizophrenia and noisiness.
Games mechanical
Pain patient insensitive to
Topology concepts of Welch
Mathematics as a model
Mathematics product of brain
Model theory of mathematical model
5270 5271
Summary: Raiffa et al. describe maths as isomorphic with real systems. 5298, 6260
Canonical equations found by Lotka
Delay (in substitution) Lotka on
Isomorphism real system and maths
5272 5273
Summary: "Will", and acting now so that certain things shall be. 6321
Conscious mind and feedback
5274 5275
Summary: On consciousness.
Pinch as test of identity
The subjective [5]: A person may be unconscious of something if he has never conceived of any variation from it 5276.
Personal notes [25]: Lazare Courtright gets from "Design for a Brain" a purely emotional message! 5276.
Summary: What good is "Design..."
5276 5277
Summary: Movement between states of equilibrium.
Summary: "Yes-no" is a language capable of explaining, or getting, all things, however complex.
The Conditioned Reflex [45]: Conditioned reflex probably works by going from equilibrium to equilibrium. 5278.
Summary: Program.
DAMS (Dispersive and Multistable System) [96]: DAMS resumed, in Aug '56, after neglect since Mar '53. 5279.
Personal notes [27]: Program for the next ten years, as seen in 1956 5279.
5278 5279
Summary: Selection cannot proceed quickly, by dichotomising, in a class that is undefined.
Summary: Example of a case in which information about the initial state gets lost.
Absolute system decay of information
Information example of decay
Initial state decay of information regarding
5280 5281
Summary: Science forswears direct knowledge in favor of the indirect.
Epistemology [54]: Primary knowledge is the "raw feel". Science seeks secondary knowledge - the patterned and communicable, which consists only of higher relations among the raw data. 5282.
The subjective [6]: The primary data are in the raw feelings. Science works only in higher relations between the raw feelings, for only the higher relations are communicable. 5282.
Summary: "Statistical machine" has two widely different meanings.
Machine "random", two types
Random two meanings
Statistical mechanics two types
5282 5283
Adaptation speeding up adaptation
Fringe
Habituation as cause of rapid adaptation
Speed (of adaptation)
5284 5285
Summary: Fast adaptation can be a manifestation of habituation. 5287.7, 5288, 5342
Summary: How to sample equilibrium states.
5286 5287
Fringe extension of
Summary: The fringe-variables of a system (in this world) are an unbounded set. 5292, 5330
Cortex combinational dynamics of
5288 5289
Summary: Learning structure by habituation to a constraint. Appalling! Habituation is not to a constraint - the ideas have no relation. 5294.4, 5313.3
5290 5291
Summary: How to join motor (and sensory) nerves to a network of part-mechanisms. Now read 3420 and see how much I have advanced in five years!
5292 5293
Summary: Adaptation always consists of one level working with a lower level as units.
Play and structure of environment
Summary: In a statistical system, habituation must be used first, in order to provide the permanent entities among which alone trials are worth conducting.
5294 5295
Summary: Why random play should come before serious learning.
Axiom the Brick
Brick axiom stated
Reducibility getting
Higher geometry of fields and matrix theory [28]: Transforming a matrix to reduced form 5297.
5296 5297
Summary: Finding a way of getting a matrix reducible.
Theory of nature of
Summary: What is a theory? Cf. Reprint 144
Model nature of
5298 5299
Egyptian steam engine protocol
Machine ancient Egyptian
Protocol Egyptian Steam Engine
Steam engine ancient Egyptian
Summary: Abstract machinery.
5300 5301
Chess machine for
Summary: How to make a brain.
Interaction small in multistable systems
Retroactive inhibition condition for zero retroactive inhibition
5302 5303
Summary: The multi-stable system must have low interaction on the average. 5312
Summary: On the pains of learning.
Dentist
Learning necessity
The Multistable System [104]: "To accumulate memories that are not affected by intervening events" is equivalent to "There must be small interaction between the events and the memories" 5304.
Constraint and structure
Hierarchy (of Bourbaki) and constraint
Structure as constraint
5304 5305
Summary: Structure is a form of constraint. 5314, 5496
Summary: To evoke a property, the designer vetoes its negation. 5316, 5331.5
Veto the basic power
5306 5307
Basin distribution of size
Machine random machine
Mapping random
Rubin and Sitgreaves' set of transformations
Trajectory distribution of length
Transformation random
5308 5309
5310 5311
Memory and internal connexions
Summary: Cross connexions, immediate effects, random transformations, and memory.
Experience and learning structure
Structure and Law of Experience
5312 5313
Summary: If structure is present in the (set of) inputs, it will turn up in the (set of) states induced by the law of Experience. 5437, 5322
Summary: A reason why a chess-player will automatically tend to learn quick ways of winning.
Feedback favours quick adaptation
Speed (of adaptation) factor for rapidity
The Multistable System [105]: A factor making for fast adaptation 5314.
Pleasure is less effective that pain
Success less effective
5314 5315
Summary: Fixing the step-mechanisms on the occurrence of 'success' adds little to the resources of an ultrstable system. 5331.5
Transformation semi-random, many equilibria
5316 5317
Basin model with lots
Equilibrium randon transformation with many
Field (of substitution) cutting into small basins
Summary: How to chop up a field. 5408, 5524
Personal notes [28]: First advert of "Introduction to Cybernetics", 5319.
5318 5319
Structure learning external structure
Equilibrium and transfer of "structure"
5320 5321
Summary: How does the child get "stucture" from the world around it? It can't keep it out!
Copying child and structure
5322 5323
Summary: The "structure" developed by the child (as a result of structure in the world) need not copy the world's structure.
Summary: I need not worry further about reversibility.
Machine never reversible
Reversible process no process is!
Curie's principle
5324 5325
Variety decay of
Summary: Curie's principle is merely a special case of my decay of variety.
5326 5327
Chess analysing ahead
DAMS Mark II (Dispersive and Multistable System) [3]: For a machine to "study a move ahead" it has only to be affected by its "provisional" output. 5328.
Summary: "Looking one move ahead does not require special programming.
5328 5329
Fringe
Summary: On the size (duration) of a significant step. 5288
Success less effective
5330 5331
Summary: If punishments only are used, zero punishment is equivalent to reward.
Pain is sufficient
Summary: Selection and elimination.
5332 5333
Discrimination in feedback, no general rule
Information depends on set
5334 5335
The Multistable System [106]: There is no general rule for how the feedback should be made discrimminating. Only when a particular machine is given can the question proceed to detail. 5336.
Summary: There is no general rule for characterising the more efficient forms of corrective feedback. 5369.2, 5371, 5417, 5539
5336 5337
Transformation moving sequentially
DAMS Mark II (Dispersive and Multistable System) [4]: Effect of a transformation being carried out sequentially, (so that e.g. x'2 depends on x'1, rather than x1) 5338.
Summary: Effect of computing a transformation sequentially.
Training of full efficiency
Trial and error of full efficiency
5338 5339
Summary: Train by situations so matched to the system's present ability that feedbacks of "right" or "wrong" are equally likely.
Feedback of full efficiency
Summary: There is no general machine that can be specialised, only a class of individual machines. It is the class that can be broad or narrow. 5507
Machine no general machine, only class
5340 5341
Ultrastability bias to efficiency
The Multistable System [107]: The multistable system has a bias towards becoming efficient and quickly adapting. 5342.
Summary: The ultrastable system has an intrinsic bias towards efficiency and quickness in learning.
Black box, problem of the poorly observable black box
Isomorphism Moore's definition equals mine
5342 5343
5343+01 5343+02

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