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

Ergodism Ergodic systems Information Wiener on 2517 2518

Summary: Stability of a chain-circuit of variables. (See also 2604) The Conditioned Reflex [5]: Conditioned reflex machine built. 2614. Seems to be original, 2623. Summary: Inaugural meeting of the Ratio Club at the National Hospital for Nervous Diseases. Information in time series 2623 2624

Bit (= binary digit) quantities in speaking etc Homeostat new possibility Information quantitative examples Delay (in substitution) and oscillation Society [30]: Oscillations in fly population and its cause, 2784. 2783 2784

Code types of Genes as information Information in genes 2785 2786

Baudot code Information in genes Summary: Information theory. Pattern (in general) recognition of 2819 2820

Summary: Canonical equations of systems composed of units each of which tries to make itself (its dial value) some function of the others. (3200) Society [35]: Equations of a society in which each unit tries to maintain itself at some function of its surroundings 2991. Summary: The system that does not generate information is identical with an absolute system. 3032 Information the noiseless system Oddments [28]: Is the absolute system 'noiseless'? 2992, 3013, 3031, 3060. 2991 2992

Summary: Necessary and sufficient conditions that a first adaptation should be still present after a second has taken place. Oddments [28]: Is the absolute system 'noiseless'? 2992, 3013, 3031, 3060. Information the noiseless system 3031 3032

Summary: Systems that are partly stochastic. Density in phase in absolute system Information and density in phase Statistical mechanics density in phase 3099 3100

Summary: The basic equations of statistical mechanics (Continued 3134) Black box, problem of the conjuring as Information effect of threshold Threshold and information 3105 3106

Summary: Darwinian mechanisms are to be developed by Darwinian process. Information gate admitting Switching as a gate admitting information 3151 3152

Summary: Switches that see a Markoff process only through themselves: consequent bias in their settings. (Theory in metric-less states, 4527) Markov process / chain seen through a gate or switch Stochastic processes seen through a gate or switch Information in machines 3163 3164

Information in machines Information in machines 3165 3166

Information in machines Information in machines 3167 3168

Information in machines Summary: In an absolute system formed by the junction of independent parts, if a particular part can take one of ρ initial states and can show σ lines of behaviour from each initial state, then the quantity of information log2 ρ + log2 σ cannot be exceeded whatever part has been chosen. Information in machines 3169 3170

Density in phase in absolute system Information in machines Information in machines 3171 3172

Summary: Information in an absolute system always falls to log2 η* (3176) where η is the number of the system's stable states and cycles. *Allowance should be made for the fact that the resting states are not equally probable. Information in machines Information in machines 3173 3174

Information in machines Summary: Information in a machine. The catchment area of a resting state. Information in machines 3175 3176

Summary: Information in a conjoined system. 3274 Information in machines Information organisms aim to destroy it Information in machines Markov process / chain passing through transducer 3177 3178

Information in machines Information in machines 3179 3180

Summary: Example and proof of Shannon's Theorem 7 Information in machines Information in machines DAMS (Dispersive and Multistable System) [13]: Possible patterns for joining output and inputs, 3182, 3237. 3181 3182

Information in machines Information in machines 3183 3184

Information in machines Information in machines 3185 3186

Information in machines Information in machines 3187 3188

Summary: Networks for DAMS. (Cf. 3237) (Further example 3306) Information in machines Information in machines 3189 3190

Information in machines Information in machines 3191 3192

Summary: Information in machines. Information in machines Information in machines 3193 3194

Information in machines Information in machines Markov process / chain affecting a machine 3195 3196

Information in machines Markov process / chain affecting a machine Information in machines Markov process / chain affecting a machine 3197 3198

Information in machines Markov process / chain affecting a machine Summary: Shannon and I. Chasing equation of Coding in machine Constant intrinsic stability definition Equilibrium 'constant intrinsic' Information in machines Markov process / chain affecting a machine Output as function of input Transformation function-forming 3199 3200

Summary: A variable of constant intrinsic stability and one that always moves towards some function of its neighbours' states are identical. (Cf. 3110) (Behaviour 3134, 3239) Information in machines Markov process / chain affecting a machine Information in a disturbed system Information in machines Markov process / chain affecting a machine Parameter as source of information 3201 3202

Summary: Passing information from parameter into machine. The previous theorem can be improved. Here is a better statement... Information in machines Markov process / chain affecting a machine Information in machines Markov process / chain affecting a machine 3203 3204

Summary: Accurate statement of the amount of information that can be put into a machine by arbitrary interference. (3275) Information in machines Markov process / chain affecting a machine Summary: A physical example of habituation. Habituation physical example Information in machines Markov process / chain affecting a machine 3205 3206

Summary: In the field of an absolute system, every convergent junction acts as a sink for information. Information in machines Information lost by convergence in field Markov process / chain affecting a machine Information in machines Markov process / chain affecting a machine 3207 3208

Summary: Maximal loss at a convergent point in a field. Table of log2[(aa bb)/(a+b)a+b]. Information in machines Markov process / chain affecting a machine Summary: We cannot measure information by finding contributions from sub-ensembles and adding. (Another example 3249) Information belongs to the whole system Information in machines Markov process / chain affecting a machine 3209 3210

Information in machines Markov process / chain affecting a machine Summary: An absolute machine can never gain more information than is put into it. Information in machines Markov process / chain affecting a machine 3211 3212

Information in machines Markov process / chain affecting a machine Summary: When a parameter affects a machine, the gain in information is stationary (and a maximum) if the parameter's values are distributed independently of the machine's. Information in machines Markov process / chain affecting a machine 3213 3214

Information in machines Markov process / chain affecting a machine Summary: Passage of information as machine dominates machine. (See 3298, 3218, 3275) Information in machines Markov process / chain affecting a machine 3215 3216

Capacity information Channel capacity of absolute systems Information in machines Markov process / chain affecting a machine Transmission capacity of absolute systems Information in machines Markov process / chain affecting a machine 3217 3218

Information in machines Markov process / chain affecting a machine Summary: (Stated at the front - on 3218): If a machine is driven by an absolute system, the duration of coupling makes no difference to the amount of information received. Information in machines Markov process / chain affecting a machine 3219 3220

Information in machines Markov process / chain affecting a machine Summary: An information source controlling an otherwise absolute system raises it to a definite information content at which it is in stable equilibrium. (3086) (Canonical equations next page) Information in machines Markov process / chain affecting a machine 3221 3222

Information in machines Markov process / chain affecting a machine Markov process / chain equilibrium in ensemble Parameter as source of information Resting state of system with Markoff parameter Summary: Canonical equations of the densities in state of a system disturbed by an information source. (See 3227) Information in machines Markov process / chain affecting a machine 3223 3224

Information in machines Information of transition Markov process / chain affecting a machine Summary: Another measure of information applicable to a machine. Information in machines Markov process / chain affecting a machine 3225 3226

Information in machines Markov process / chain affecting a machine Summary: When driven by a steady statistical source, the information in a machine does not tend to a minimum. Information in machines Markov process / chain affecting a machine 3227 3228

Information in machines Markov process / chain affecting a machine Statistical mechanics states that cannot be escaped from Summary: States that lock accumulate all the members of the ensemble. 3233, 3291, 4524 Information in machines Markov process / chain affecting a machine 3229 3230

Information in machines Markov process / chain affecting a machine Information in machines Markov process / chain affecting a machine Transition probability between resting states 3231 3232

Information in machines Markov process / chain affecting a machine Summary: Information when a stochastic parameter changes infrequently. Information in machines Information ways of loosing Markov process / chain affecting a machine 3233 3234

Summary: Ways of losing information. 3274 Information in machines Information in machines 3235 3236

Summary: Wiring pattern of DAMS. Information in machines DAMS (Dispersive and Multistable System) [13]: Possible patterns for joining output and inputs, 3182, 3237. Information in machines Resting state maximal number 3237 3238

Information in machines Summary: Conditions that a machine shall have the maximal number of resting states. This can be specified further... Information in machines 3239 3240

Summary: Maximal number of resting states. (3308) Information in machines Summary: Information when A drives B. Information in machines 3241 3242

Absolute system why not x=f-1 (x')? Canonical equations why not [x=f-1 (x')]? Information and canonical equations Information in machines Summary: The inverse of the canonical equations. Experiment when it stops Information and experiment Information in machines 3243 3244

Summary: An experiment stops when the exchange of information has reached equilibrium. (3248, 3254, 3691) Information and experiment Information in machines Epistemology [5]: When does an experiment stop? 3245. Independence and information Information and independence Information in machines 3245 3246

Summary: Independence does not in general cause loss of information. (3274) Information in machines Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3247 3248

Summary: Entropies in the parts do not sum to that of the whole. Entropy of a part may equal that of the whole. Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Summary: Information and experiment. Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3249 3250

Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3251 3252

Summary: Information in an absolute machine. [deleted] Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3253 3254

Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3255 3256

Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3257 3258

Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3259 3260

Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3261 3262

Summary: Information and the experimenting on dynamic systems. Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3263 3264

Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Summary: This then is the maximal information obtainable in an absolute system of σ states by starting it at a state selected arbitrarily and then observing how it's behaviour goes from state to state. Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3265 3266

Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3267 3268

Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Summary: Information always decreases, step by step, as an unknown line of behaviour unfolds. Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } 3269 3270

Summary: Uncertainty about the details within a line of behaviour is independent of whether that line, or some other, will occur. 3274 Experiment when it stops Information and experiment Information in machines Epistemology [6]: Passage of information from machine to observer, { 3248 - 3271 } Latent roots distribution of 3271 3272

Information and machines, collected 3273 3274

Summary: The longer the line of behaviour, the higher the chance of step-function change. Information when only part is observed 3297 3298

Summary: Information in machines. Information in a continuous system 3301 3302

Summary: The continuous system can gain information though absolute. Summary: As soon as a sub-system is isolated it starts losing information. Information in a sub-system Personal notes [13]: Discussion with Wiener, May '51. 3304. 3303 3304

Entropy calculation of Information calculation of Markov process / chain information from Transducer theory of 3368 3369

Summary: Information going through a transducer. Information through a transducer Transducer destroying information 3376 3377

Information necessary for resting states Resting state and information Transducer destroying information 3403 3404

Summary: A machine's tendency to destroy or conserve information (as uncertainty of state) depends slightly on certain necessary factors in the parts but depends more on the holistic factor of assembly. Information destruction in machine 3405 3406

Information destroyed by part function Latent roots distribution DAMS (Dispersive and Multistable System) [22]: DAMS must contain its information reduntantly 3419. Cortex, sensory layering in DAMS (Dispersive and Multistable System) [23]: DAMS' variables must be arranged in layers at its sensory input, in order not to lose information, 3420. 3419 3420

Summary: History of DAMS. Summary: Sex and the Multistable System Natural Selection [5]: There are two sexes so as to bring together all mutations. Each valve in DAMS has two inputs for the same reason 3509. DAMS (Dispersive and Multistable System) [34]: History of DAMS: taken down for uniformisation, 3509. DAMS (Dispersive and Multistable System) [35]: The two inputs to each value cause mixing just as do two sexes, 3509. Information nature of Redundancy organisms prefer highly redundant information 3509 3510

Campbell's theorem Degenerance, in system definition Epistemology Campbell's theorem Observable Campbell's theorem Summary: Statistical mechanics. Chess 'super' moves Homeostat variety on switches Information on uniselectors 3607 3608

Cleverness may be purely negative Selection of patterns Summary: 'Positive' cleverness may be really only what is left after the elimination of nonsense. 4578 5307.3 (See 3629) Information amplifier for 3609 3610

Summary: The mechanism underlying paranoia. Aggression relation to paranoia Information and resting states Resting state and information DAMS (Dispersive and Multistable System) [52]: The resting states of DAMS are not accessible unless a rich source of information is available and a broad channel into it, 3656. 3655 3656

Summary: The number of resting states that a machine can display to an observer depends on the information that the observer can get into the machine. (Next page) Stimulus information in Information in primary operation Primary operation information admitted 3657 3658

Information in canonical equations 3659 3660

Experiment when it stops Information from machine to machine 3690 3691

Information in partition Partition information in 3694 3695

Summary: Searching, random and systematic. Information first amplifier Summary: Qualification to 3746. 3752 3753

Summary: Rank of the differential matrix, and null-functions. Rank and reducibility Reducibility rank of Information retention by null-function Null-function and retention of information 3772 3773

Control via constants Jacobian (determinant) rank and control Parameter independence among Information loss in function 3778 3779

Determinate meaning of Set or Ensemble relation to 'determinate' Summary: Field + field, and determinate changes of parameter. Summary: The observer-system relation is symmetrical; so we can calculate 'information' over an ensemble of observers Experimenter information to Information to experimenter 3786 3787

Information in vector Rank and resting state Resting state rank around Summary: Information, rank, equations. 3799 Experimenter testing independence Experimenter using primary operations Independence testing for 3788 3789

Summary: On the operation that brings the representative point to a particular initial state. 3846, 4628 Convergence (of lines of behaviour) Independence and convergence Independence types of Information convergence and Invariant three types 3792 3793

Summary: Convergence of lines as invariance. Experimenter receiving information Information transfer of 3794 3795

Isomorphism of science Information chain of systems 3802 3803

Summary: Habituation. 3837, 3842, 3856, 4526 Dispersion defined by information Independence definition Information and independence and dispersion Essential variables possible mode of action 3824 3825

Summary: Other things being equal, the system with more step-functions will have more resting states. Information decay of Natural Selection [51]: Importance of the fact that the world is old, 3857. 3856 3857

Summary: Return of parameter to a previous value can cause further loss of information. 3863, 3954, 4057, 4074, 4373 Information fall under change of parameter 3862 3863

Summary: Topology of absolute system. Summary: 'Stability' must be re-stated in terms of information. 3963, 3980, 3975 Genes should receive no information Information genes should get none Unsolved problems [13]: 'Stability' should be re-stated in terms of information, so as not to raise the unwanted 'unstable' equilibria. 3929. 3928 3929

Summary: Self-reproducing arcs are of very great importance, for good or evil. Review 4154 The Multistable System [40]: Self-reproducing arcs are of high importance, for good or evil 3932. Information in partition Partition information in 3932 3933

Basin and habitation Summary: Administering a determinate impulse to an ensemble can only cause its information to fall. 3954 Basin defined Information and d-impulse 3936 3937

Step function topology of Summary: Unsolved problem. 3959, 3962 Information must be destroyed 3938 3939

Summary: Partition and lattice. Summary: Partitions in absolute ensembles. Information and lattice theory 3950 3951

Experience Information fall under change of parameter Parameter allows information to fall 3954 3955

Summary: A quite different way of defining and handling the absolute system. 3962, 4019. Review, 4338 Information levels of Information what is necessary 3960 3961

Summary: Why do our brains take so much notice of a step-function? 4233 Unsolved problems [14]: Why do we take so much notice of a step-function? 3994. (because of its 1-bit simplicity). Summary: 'Absoluteness' is relative to an observer. 4031, 4043. Information levels of 3994 3995

Class I.e. not to individual Congruence Ideal (mathematical) Information 'complete' within limits Quotient machine and residue class Residues (of congruences) Summary: Residue classes in behaviour. Basin as partition Partition lattice theory 3996 3997

Summary: The representative point may be divided into parts, as the whole system is thought of in parts. Information destruction of Summary: More on information. 4133 Design for a Brain first advert Personal notes [18]: First advertisment for "Design", 4123. 4122 4123

Summary: Runaway and information. 4303 Information at runaway 4156 4157

Summary: Effectiveness of parameters with finite substitution. Applied 4414 Dimension of parametric control History examples Memory in system Parameter control exerted by Summary: Examples of states that include history. Summary: Knowledge must be tested by control. 4438 Information at runaway Epistemology [17]: Knowledge must mean 'control' if it is to be objective, 4303. 4302 4303

Summary: A system can "know" by having the right values of variables or parameters. 4438 Knowing as selection of vector Summary: When a designer makes a machine of n states and a parameter-combinations, he puts in variety of a.n.log n This is its intrinsic content. 4463, 4704 Information in machine 4428 4429

Summary: Trial and error in reaction to shock. Summary: Information in printed English. Information per word Memory information in 4432 4433

Entropy computing Information computing Summary: Computing entropy. 4444 4445

Summary: One formulation covers "design" "input" and "noise". (Next section) 4449 Design nature of Information in machine Epistemology [24]: Distinction between 'design' and 'input' 4449. 4448 4449

Summary: A single machine contains many "informations", most of which do not interact with the others. Example 4577 Information two need not interact Summary: Joining absolute systems without metric. Example 4473, 4498, 4733 Joining general theory 4470 4471

Distinguishability in brain Information conservation in chain 4502 4503

Genes reproduction of Information on chromosomes Summary: How chromosomes reproduce themselves. High survival power. Natural Selection [78]: Reproduction of genes; extra survival power given by combination in pairs 4523. 4522 4523

Topology necessity for Summary: Poincaré on the study of functions. Information two need not interact Linkage Meccano linkage 4576 4577

Summary: 'Equilibrium' refers to a state, 'stability' to the region around the state. Basin Traffic principle nature Summary: Properties of metric-less system. 4623 Continuity as constraint Information in stimulus Stimulus information in 4596 4597

Summary: Entropies in regulation. 4666, 4722, 4971 Capacity for control Information and entropy 4664 4665

Summary: Error-controlled regulation is possible only by blocking conduction. Information and observer Epistemology [34]: When variety arrives, the observer who sees all sees unity changing to diversity; the element in the set sees diversity change to unity. 4691. 4690 4691

Information flows in homeostat Selection and variety Switching switching off 4706 4707

Control of system that learns Learning during regulation Summary: Observations on controlling a system that can learn. Design and variety Information variety is sufficient Variety and information 4780 4781

Summary: The limit of progressive regulation. Amplifier limit of Regulation limit of Control as reduction Equilibrium and information Information as reduction Regulation and information Selection and information Survival in set theory 4794 4795

Summary: Adaptation in evolution. Constraint and natural law Information Goldman on Quotations [53]: Goldman on Science as a use of Constraints 4866. Summary: Quotations. Quotations [54]: "A study of the real world thus becomes a study of transducers." 4867. 4866 4867

Differential equation stability theory of Equilibrium Bellman on Equilibrium complexity of Information partial Knowledge partial Stability stability theory of differential equations Summary: Bellman on 'stability'. Trajectory stability of 4914 4915

Summary: Trials are good, for they bring information. 4945, 4948, 4965, 4963 Information by trials Trial and error gives information Behaviour all reducible to behaviour Thing as way of behaving 4942 4943

Summary: Discriminative feedback. 4963 Summary: Information repair. Information "repair" (MacKay) Information and discriminative feedback Summary: Letters as Markov chain. Adaptation strategy of Markov process / chain English as Maximal likelihood and adaptation 4946 4947

Convergence (of lines of behaviour) in random transformation Information in random machine Transformation random Variety and random transformation 4974 4975

Summary: With a random transformation the variety tends to fall to two thirds at each step. Qualified 5158 Information blocking 4978 4979

Organisation emergent properties Summary: Whether properties "emerge" or not depends on our knowledge of the parts. Summary: Why information? Energy an old question Information and energy 4986 4987

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

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

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: 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

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

Discrimination in feedback, no general rule Information depends on set 5334 5335

Channel capacity crowding within Information loss by crowding 5372 5373

Summary: Constraints are found by applying information-losing transformations and seeing whether they are still acceptable to the essential variables. 5756 Constraint finding Information advantages of losing 5728 5729

Information more than 1 man-lifetime Regulation and reducibility 5792 5793

Summary: Some systems are not to be understood, or controlled, by the amount of information that can be accepted in 1 man lifetime. 5810 Information direction is irrelevant Summary: The symmetrical relation between transmitter and receiver, of McGill and Garner and Woodward, is: between two variables' variations a constraint has been perceived. 5820 Constraint information as Protocol constraint in 5794 5795

Summary: In the cortex, study only the unspecialised case. Information loss through net Network transmission through 5830 5831

Information amount in theory Model has two informational measures Summary: Every theory has two informational aspects: its passive, when it is learnt or otherwise acquired; and its active, when it is used as transducer. The two qualities of information are not linked necessarily. 6010 6011

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

Information in a set of functions Laplace transformation in set theory 6036 6037

Summary: Finding how much information there is in a brain. Information how much in brain? 6048 6049

Equivalence relation information in Homomorphism variety of Information in equivalence relation 6170 6171

Information Reza's book Topology Bushaw's book Evolution ensures extinction! Genes no unique pattern Survival evolution prevents! Natural Selection [89]: Selection intensifies selection. Simpson, 6469. 6468 6469

Summary: Any selection of 1 from more than 101000...(47 zeros)...0 is physically impossible. Bremermann's limit another form Information in a mapping 6546 6547

Summary: How information-quality can explode when complicated at the sensory side. 6549 Non-linear systems information in Summary: Length of sequence increases the uncertainty exponentially. Information when input is a sequence 6548 6549

Summary: To be able to compute a function by a few variables at a time is a (non-trivial) restriction. Information in continuous waveform Summary: Information in a continuous waveform. 6612 6613

Information loss, in "mesa" phenomenon Mapping destroying information 6642 6643

Information loss, in conditioned reflex Reflex, conditioned information loss Summary: Pavlov, p.197 Summary: Events that show mutual exclusion in their behaviours may be called a "variable". Variable nature of 6726 6727

Summary: Group therapy in kinematic graphs. 6811 Information axioms of Summary: Axioms of information theory. Cylindrance and reducibility Explanation cylindrance of Relation Five-fold 6770 6771

Summary: Exchanging variables for cylindrance. Information in regulation, Conant Summary: Collection of some ways of transforming a space and affecting cylindrance. 6830 6831

Summary: Studying mechanisms that are "dynamic" demands far more information than those that are more of the "static" type. Dynamic system information in, v. static Information dynamic versus static systems 6906 6907

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

Coding of machine to machine Coordination machinery for coordination Information in regulation, Conant Transducer for coordination Summary: Machinery for coordination. 6940 6941

Summary: (1) The "transmissions" require for coordination can always be achieved - method given. (2) The whole flow of information can be analysed by the methods of book-keeping. Another analysis: 6997 Analysis of information flow Coordination minimal information for Information partitioned Partition of information flows Transmission minimal, in coordination Summary: High order interactions can readily occur in physical systems. 7006 Coordination minimal information for Interaction in physical systems Transmission minimal, in coordination 6950 6951

Analysis of information flow Coordination minimal information for Information partitioned Partition of information flows Transmission minimal, in coordination Summary: Information flow for control and coordination. Cf. 7165 Coordination minimal information for Transmission minimal, in coordination 6962 6963

ASS (Automatic Self-Strategizer) information flow in Information flow in ASS Summary: The flow of information, control, and decision when ASS (automatic self-strategizer) produces a legal and winning play. 6989, 6996 Hover mouse here to display note 6974 6975

Information the identities of Multinomial measure of information 7018 7019

Information Cause analysis 7027 7028

Summary: Transmission enters when an unordered set is distributed over a product space. Example 7092 Self-awareness in chimpanzee Summary: Self-recognition. Information in design 7088 7089

Information in pulse and gap Summary: No-pulse may carry more information than pulse. 7094 7095

Summary: Why allowing interaction boosts up informational demands. 7122, 7127 Information and interaction 7096 7097

Summary: Example of how much selection is required to make a system stable. Information required for stability Stability information needed 7106 7107

Summary: Interaction between parts having inputs raises the complexity by x ki. i = number of inputs to each part; k = number of values (states) of each part). Information and interaction Interaction increases information by x ki Summary: Me and my brain in dreams. Dream and "self" Self-awareness impossible 7124 7125

Summary: Transmission cannot be created. 7146 Conservation of Complexity Law of Transmission cannot be created Information and interaction Interaction squares it (doubled size) Size, effect of on information 7126 7127