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

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

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

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

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

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

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

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

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

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

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

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

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

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