OPERATION LOGIC - A DATABASE MANAGEMENT OPERATION SYST~ 
OF HUMAN-LIKE INFORMATION PROCESSING 
V~clav Pol~k and Nad~da Pol~kov~ (in memoriam) 
Z~vod v~po~etD/ techniky ~SAD, Brno, Czechoslovakia 
The paper contains the description of a database mana- 
gement computer operation system called operation logic. This 
system is a formal logic with well-deflned formulas as se- 
mantic language clauses and with reasoning by means of modus 
ponens rules. There are four frames - CLAUSE, QUESTION, 
I:~O~T.~, SYST~. Each of these frames is processed by one 
program. By means of these programs it can be realized under- 
standing of any clause, answering any reasonable question, 
solving az~7 reasonable problem and understanding any organizat- 
lonel structure. Some algorithms of operation logic are de- 
scribed and examples of clauses are exhibited. Our approach 
is the following: 
(1) Information processin~ of sub teots~ Material objects 
are anorganic objects or organic ones. They are also non-live 
objects or live ones. Live objects reproduce themselves auto- 
nomously. Live objects are organic individuals or artificial 
ones. Organic individuals are one-cellular or multi-cellular. 
They are also heterotrophic (they consume organic objects) or 
autotrophic (they consume anorganic objects only). Multi-cell- 
ular autotrophic organic individuals are called pl~ts. Multi- 
cellular heterotrophio organic individuals are called sub teots. 
Plants have no moving organs and no consciousness. They do 
not need them. Subjects have moving organs and consciousness. 
They need them for searching, hunting and escape. Each sub- 
Jects has general knowledge database. It contains information 
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about types of scenes (called image-frames) in the form the 
scenes are seen by the subject by its eyes, but in a very 
simplified form. It contains also sequences of scenes (called 
sceneries ) representing rules (called mgdus ponens rules) 
according to which changes in the universe are realized. Each 
subject has concrete knowledge database representing history 
of life of the subject and image-frame of actual scene~ Each 
subject constructs possible scenes and realizes program, ed 
behaviour of itself. Each sub, sot has information processing 
database mans~ament operation system having both above data- 
bases in long term memory ~nd processing actual knowledge in 
short term memory. A subject is called human, if it is able to 
describe scenes by means of processes (i.e. to decode image- 
-frames into formulu (called clauses) representing processes) 
and if it constructs ~ew clauses from the old ones by means 
of modus ponens rules (called reasonS). Subjects with consci- 
ousness without above properties are called animals. Humans 
operation system for information processing is called o e_~.e~- 
ion logic, humans clauses form & system called semantic 
language. Humans have the ability to exchange information 
among themselves by means of clauses (such activity is called 
di~o~). We have thus the following stages of information 
processing: First there are anorganic objects only. Then organ- 
ic objects appear by a random. Then by means of natural select- 
ion one-cellular heterotrophie organic individuals (bacteria) 
appear. From bacteria one-cellular autotrophic organic individ- 
uals are developed (cyanoph¥cae). Prom bacteria more sophlsti- 
c~ted one-cellular heterotrophic protozoa are developed and 
by symbiosis from protozoa and cyanop~vcae one-cellular auto- 
trophic al~ae appear. From algae plants are developed and from 
protozoa animals. From animals humans are developed (namely 
because of necessity of exchange information in social product- 
ion activities). 
(2) Semantic la~a~a~e clause. In each scene there are 
individuals (like TREE, JOHN, FEAR) and processes (like TO-GO, 
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TO-EXPLAIN). Names of individuals are called atomic individu- 
al__.ss (or nouns), names of processes are called verb__._~s. In each 
process participating individuals play Certain roles (called 
individual members) like (TO-GO WHO WITH-WHOM), (TO-EXPLAIN 
WHO WHAT TO-WHOM). Individuals have properties (like BLUE, 
EMPTY). Processes have properties (like QUICKLY, DAILY). Pro- 
pertiee of individuals are called attributes, properties of 
processes are called adverbs. Names of attributes are called 
atomic attributes (or adjectives), names of adverbs are call- 
ed atomic adverbs. There are several types of adverbs (called 
Bdverbial .members), each of them describes the circumstances 
the process is realized. The process is realized in euclidean 
three dimensibnal space (NHERE-PLACE,WHERE-NEAR, WHERE-FAR, 
~IERE-INSIDE, %~-/~E-OUTSIDE, ~CdF.~%E-BESIDE, WHERE-LEPT, WHERE- 
-HIGHT, V~RE-BEPORE, WHERE-BEHIND, WHERE-BELOW, WHERE-ABOVE, 
~-AROUND, VP~ERE-A~ONG, ~/tEaRET~F~N, FROM, TO, VIA, 
DISTANCE) in linear time scale (WHEN-ANTERIORITY, WHEN-SIMUL- 
TANEITY, r~N-POSTERIORITY, BEGI~ING, END, FREQUENCY, DURAT- 
ION) under validity of several modus ponens rules (CAUSE, 
RESULT, PURPOSE, CONCESSION) with instruments (BY-MEANS-OF) 
and acoordinE to algorithm types (BY-~AT-WAY, INTENSITY, 
RESEMBLING). Hence we have (ATOMIC-INDIVIDUAL (ATTRIBUTE 
(K))K) for individuals (such form is called compound individ- 
ual) and (VERB (INDIVIDUAL-~3ER(I))I (ADVERBIAL-MEM~ER(J))J) 
for processes i.e. for clauses. Modus ponens rules are of the 
form (IF CLAUSES THEN CLAUSES). Individual can be atomic indi- 
vidual, compound individual, process-as-individual clause, 
meta-level clause. Adverb can be atomic adverb, individual, 
adverb-defining clause. Attribute can be atomic attribute, 
individual, attribute-defining clause. To each clause some 
information about the whole clause belongs (called clause 
parameters). Individual members and adverbial members are 
called clause members . Hence we have (VERB CLAUSE-MEMBERS 
CLAUSE-PARAMETERS) • 
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(3) Clause Dar~neters. 
(a) Conte~tuatit ~. Because of existence of short term 
memory one must distinguish in each clause the old knowledge 
(called topic) and the new one (called focus) receiving thus 
either (TOPIC-VERB TOPIC-CLAUSE-HEMBERS FOCUS-CLAUSE-M~BERS) 
or (POCUS-VERB TOPIC-CLAUSE-MEmBERS POOUS-CLAUSE-~Y~S). 
(b) Tense- Because individuals, adverbs and attributes 
can be clauses, we have for each clause a graph tree with 
clauses as vertices and to-be-superior-clause-of as edges. 
One needs only relative binary time relations (anteriority, 
simultaneity, posteriority). We consider time of construction 
of the clause and time of clause process realization. Time of 
construction of meta-level clause is the time of process real- 
ization of the superior clause. Time of construction of clause 
of other types is the time of construction of its superior 
clause (or in the case of top clause - the time of sending it 
by sender). Other binar~ time relations (if needed) can be 
given by time adverbs. 
(c) Quantifiers. The simplest way in using quantifiers 
is to have only ALL and SOME with areas given in attributes. 
(d) ~ot~ The negation is used only in building scenes: 
We have old knowledge about scene. We expect new knowledge. 
We add new knowledge. We negate expected but untrue knowledge. 
Prom this we have the followingz either we negate new expected 
focus (i.e. focus with or without verb) or we negate topic 
verb only. 
(e) Aspect s iterativness I extension m process realizati~: 
Each process according to its completness can be COMPLETED or 
NOT-COMPLETED, according to its iterativness REPEATED or NOT- 
-REPEATED, according to its relation to ~a certain time moment 
I~IATE or EXTENDED and according to its realization 
REAL-PROCESS, UNREAL-PROCESS-POSSIBLE-SCENE-DEFINING or UNREAL- 
-PROCESS-POSSIBLE-SCENE-NOT-DEFINING. 
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(f) Sub.jective modalit~: (CERTAINTY: I know that CLAUSE), 
(HOPE: I suppose that CLAUSE), (INDETER~INATION: I don't know 
that CLAUSE), (DOUBT: I suppose that NOT-CLAUSE), (NEGATION: 
I know that NOT-CLAUSE). 
(g) Emotlonalit2: (OBJECTIVITY: I am indifferent to 
realize CLAUSE), (PLEASURE: I want CLAUSE, I know that CLAUSE), 
(LONGING: I want CLAUSE, I suppose that CLAUSE), (FEAR: i want 
CLAUSE, I suppose that NOT-CLAUSE), (ANGER: I want CLAUSE, 
I know that NOT-CLAUSE, It is CLAUSE(~) if NOT-CLAUSE, I don't 
want CLAUSE( 1 ), It is NOT-CLAUSE( I ) if NOT-CLAUSE and CLAUSE 
(2), I strive to realize CLAUSE(2)), (REGRET: dtto like for 
anger but I don't strive to realize CLAUSE(2)). 
(h) Oblective modalit2: 
(NECESSITY-WITH-SOURCE-AGENT) : Agent A is indifferent to 
CLAUSE" A realizes CLAUSE(I) if NOT-CLAUSE, A doesn't want 
CLAUSE( I ) ), 
(NECESSITY-WITH-SOURCE-NON-AGENT: Non-agent B is superior to 
A, B realizes CLAUSE(1) if A doesn't realize CLAUSE, B 
wants CLAUSE, A is indifferent to CLAUSE, A doesn't want 
CLAUSE(1), B appeals to A to realize CLAUSE), 
(NECESSITY-WITH-SOURCE-ENVIROI~ENTAL-CIRCUMSTANCES: A is in- 
different to CLAUSE, One realizes CLAUSE(1) if A doesn't 
realize CLAUSE, A doesn't want CLAUSE(1)), 
(NECESSITY-WITH-SOME-SOURCE: At least one type of necessity 
'is given), 
(PO~IBILITY-WITH-SOURCE-AGENT: Inner circumstances of A are 
complete for CLAUSE), 
(POSSIBILITY-WITH-SOURCE-NON-AGENT: B is superior to A, B 
agrees to realize CLAUSE, B realizes CLAUSE(1) if A real- 
izes CLAUSE and B doesn't agree to realize CLAUSE, A 
doesn't want CLAUSE(I ) ), 
( POSSIBILITY-WITH-S OURCE-ENVIRONMENTAL -CIRCUMSTANCES : Environ- 
mental circumstances are complete for CLAUSE), 
(POSSIBILITY-WITH-ALL-SOURCES: All types of possibilities are 
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given), 
(WILL-WITH-SOURCE-AGENT: A wants CLAUSE, A strives to realize 
CLAUSE). 
Objective modelity = n-th objective modality ((n-1)-th object- 
ive modality (... ( 1-th objective modality) ... ). 
(i) Global modalit2: INFORMATION, rIND-TRUTH-VALUE- 
-QUESTION, PIND-X-VALUE-QUESTION, COMMAND, PROHIBITION, RE- 
QUEST, ADVICE. 
(J) ~atabase position: VIEWPOINT. 
(4) Understandin~ . Clauses are grouped into role-pairs 
(WHY-ROLE-CLAUSE HOW-ROLE-CLAUSES), modus ponens rules, scenes 
and denote-clauses. Content of clauses is given by means of 
such grouping. It enables to operate with vague notions and 
even with contradictions. Each system, say S, is described by 
input and output of structures, energy and records, by struct- 
ures as means and records as database, by scenes and by role- 
-pairs, where wh~-roles are the roles being fulfilled by S and 
how-roles are why-roles of subsystems of S. Understanding of 
very large systems and semantic mathematical analysis of 
anthropoecoeystems is realized by the binary relation to-be- 
-subsystem-of defined by role-pairs on SYSTEM's. Example: 
(ROLE-PAIR(24): (WHY-ROLE: (TO-RECEIVE (WHO: IT) (WHAT: 
GLUCOSE))) (HOW-ROLE(1): (TO-REALIZE (WHO: IT) (WHAT: PHOTO- 
sn~sls) ) )) 
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