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Ross indexed the following pages under the keyword: "Machine".

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Summary: A review of Jennings' book.
Organisation of organisations
Summary: The "constants" i.e. variables whose changes make observed behaviour may themselves be activities composed of other variables. And these "constants" whose changes make.... This needs specifying from the organisational point of view. (See 1193)
Machine definition
Organisation definition
1155 1156

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Machine definition
Transformation Monograph
Set or Ensemble of machines
Transformation Monograph
4344 4345

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Transducer inverse of
Machine non-singular
Transducer non-singular
4396 4397
Summary: Information that can come from a machine.
Graph definition
Machine falls in capacity
Epistemology [22]: Estimates of how fast knowledge can be got from a machine 4430.
Entropy and information
4430 4431
Algebra Black Box as
Machine as an algebra
4456 4457

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Joining tensor calculus of
Machine Riguet's definition
Tensor product of two machines
4766 4767
Dynamic system stochastic
Machine stochastic machine
Stochastic processes in machine
Input defined
Markov process / chain the Markov machine
Output defined
Transition probability in Markov machine
4768 4769
Summary: Equilibrium of Markov chain.
Markov process / chain finding equilibrium density
Dynamic system compatible with equivalence relation
Lattice Riguer on
Machine compatible with equivalence relation
4776 4777
Compatibility machine and equivalence relation
Dynamic system "quotient" machine
Equivalence relation in machine
Homomorphism corrected
Machine quotient machine
Quotient machine by indistinguishability
Summary: Quotient machines. 4937, 5001, 5165, 5148
4778 4779
Summary: "Output to an input" is a relation of order, and may give a lattice.
Arc as partly ordered set
Cortex partly ordered arcs in
Input input to output as order
Lattice input to output lattice
Order among arcs
Output output to input, as order
Partly ordered set arcs as partly ordered set
Summary: Complex taps can be easily built by mere conjunction of many simple. 4792
Design of complex tap
Dynamic system for repetitive work
Machine for repetitive regulation
Relay design of
4788 4789
Summary: The homeostat does amplify. 4794>
Amplifier homeostat as
Homeostat amplification in
Relay design of
Summary: Designing a machine to build a machine. 4808 (top), 5070, 5072
Dynamic system dynamic system that "designs" another dynamic system
Machine designed mediately
Machine that designs machine
Epistemology [37]: Machine that builds a machine 4793.
4792 4793
Summary: Many concepts include that of "reduction". 4880, 4950, 4963
Design and information
Machine as reduction
Prediction as reduction
Problems solving problems
Property as information
Reduction many forms
Relation as information
Code military
Coding theory of
Strategy of trial and error
Trial and error optimal method
4796 4797
Summary: Strategy of trial and error. 4844, 4949
Machine is a selector
Selection by machine
Statistic trial and error as statistic
Mapping tensor power of
4798 4799
Machine defined again
4852 4853
Summary: What is a scientific "theory"? 4948
Summary: A "machine" implies two sets and a mapping; coupling requires an extra mapping. 4932, 4952, Formal statement 5097
Machine defined finally
Mapping machine as
4876 4877
Aging (as process)
Experience law of
History aging processes
Machine Markovian, aging in
Markov process / chain aging in
Variety in Markov machines
Habituation in Markov machines
4916 4917
Summary: Isomorphism and equiformality. 4990, 5000
Hierarchy (of Bourbaki) machine in hierarchy
Machine in hierarchy of sets
4934 4935
Summary: On the accessibility of states. 4953, 4968
Accessible state
Control of system
Initial state control over
Machine partly observable
Summary: The "partly observable machine with input." 4956
Epistemology [45]: "Observing" or "studying" a machine means getting sequence of inputs and outputs alternately, 4953.
4952 4953
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: The Turing machine.
Machine reproduction of
Reproduction machines for
5042 5043

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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
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: Systems that interact finitely with their observer.
Machine as constraint
Machine algebraic in protocol
5080 5081
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: Memory must fail if new information is forced in. 5205
Machine binary relation in
Relation binary, in machine
5180 5181
Canonical equations in protocol
Machine in protocol
Protocol general theory of
Summary: Constraints in protocols. 5978
Protocol general theory of
5194 5195

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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
Egyptian steam engine protocol
Machine ancient Egyptian
Protocol Egyptian Steam Engine
Steam engine ancient Egyptian
Summary: Abstract machinery.
5300 5301
Basin distribution of size
Machine random machine
Mapping random
Rubin and Sitgreaves' set of transformations
Trajectory distribution of length
Transformation random
5308 5309
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
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

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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
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
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: The unspecified machine.
Machine the fully general machine
5666 5667

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Machine uncertainty analysis of
Uncertainty analysis of machine
5820 5821
History restoring predictability
Machine incompletely observable
Memory restoring predictability
Observable incomplete
5866 5867
Summary: Transfer of constraints from the world outside to that inside.
Summary: A machine with input may correspond to an algebra.
Algebra machine and internal composition
Associativity (mathematical) and machine
Machine and its algebra
5888 5889
Machine mathematics of
Mathematics of machine
Hierarchy (of Bourbaki) machine in hierarchy
5906 5907
Summary: The notion of two machines being "similar", or even just "related", has been completely generalised.
Machine "similarity" generalised
Relation between machines
Similarity generalised
6014 6015
Summary: Eigen-theory generalised. 6109
Summary: A physical system that is not completely analysable. 6065
Information transducer that conserves
Machine information machine conserving
Reducibility irreducible systems
6032 6033

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Summary: Habituation with cycles allowed. 6108
Habituation tilde-operation
Machine generating properties
Selection by machine
6088 6089
Summary: Oscillating systems, when coupled, do not necessarily pull together in frequency.
Compatibility machine and equivalence relation
Equivalence relation and machine
Machine and equivalence relation
Summary: When a simplification is permissible. 6148, Better: 6254
Summary: Today I can say I have solved the problem I set out to solve on 7 May 1928 [31 years prior]. I asked, roughly, whence came the patterning properties of the nervous system. The answer is now clear...
6116 6117

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Homomorphism only simplification
Machine and equivalence relation
Simplicity meaning of
6148 6149
Machine as constraint
Fibonacci's series as example
6234 6235
Equivalence relation and machine
Machine and equivalence relation
Simplification of machine
6254 6255
Summary: Immediate effect is a reality-shadow reaction.
Machine as transformation of succession
Time machine as coding of
Summary: A machine is a "shadow" of simple progression.
6264 6265

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Summary: Proofs the orders of size.
Machine Gill on
Machine Ginsburg on
Summary: Indefinitely long memory in simple machine. 6470
Memory infinitely far back
6460 6461

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Machine relations compatible
Relation compatible with machine
Summary: If two binary relations are each compatible with a machine, then so is their composition.
6808 6809

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Summary: Conant's measures HL,TL,QL have the freedom from absolute value called for in the "Bio Science" paper.
Information Conant's HL,TL,QL
Library retrieval equals theorem-proving
Theorem theorem proving equals information retrieval
Transmission Conant's TL
Homomorphism of machines with input
Machine homomorphic
6926 6927
Summary: For best regulation, the environment must be a homomorphism of the regulator. But see 6934
Homomorphism proved necessary
Regulation homomorphism for maximal
Summary: Definition of homomorphic machines with input. 6936
Machine algebraic theory
6932 6933
Summary: Optimal regulation and homomorphism.
Linearly dependent process defined
Machine Turing-type
Markov process / chain and linearly dependent process
Turing machine and machine with input
Transmission in real systems
6936 6937

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