00100	CHAPTER 2--SIMULATION MODELS AS EXPLANATIONS
00200	
00300	
00400	  It is perhaps as difficult  to explain    scientific explanation as it
00500	is to explain anything else. The explanatory practices of different
00600	sciences differ widely but they all share the purpose of someone 
00700	attempting to answer someone else's why-how-what-etc. questions about
00800	a situation, event, episode, object or phenomenon. Thus explanation implies a 
00900	dialogue whose participants share some interests, beliefs, and values.
01000	A consensus must exist about admissable and appropriate questions and answers. The participants
01100	must agree on what is a sound and reasonable question and what is a
01200	relevant, intelligible, and (believed) correct answer.
01300	The explainer tries to satisfy a questioner's curiosity by making
01400	comprehensible why something is the way it is. The answer may be a
01500	definition, an example, a synonym, a story, a theory, a model-description, etc.
01600	The answer satisfies curiosity by settling belief. Nnaturally the task of
01700	satifying the curiosity of a five year old boy is different from that
01800	of satisfying a  forty year old psychiatrist.
01900	    Suppose a man dies and a questioner (Q) asks an expainer (E):
02000	       Q: Why did the man die?
02100	One answer might be:
02200	       E: Because he took cyanide.
02300	This explanation might be sufficient to satisfy Q's curiosity and he
02400	stops asking further questions. Or he might continue:
02500	       Q: Why did the cyanide kill him?
02600	and E replies:
02700	      E: Anyone who ingests cyanide dies.
02800	This mechanistic  explanation appeals to a universal generalization under which
02900	is subsumed the particular fact of this man's death. Subsumptive explanations
03000	satisfy some questioners but not others who, for example, might want to
03100	know about the physiological mechanisms involved.
03200	       Q: How does cyanide work in killing people?
03300	       E: It stops respiration so one dies  from lack of oxygen.
03400	If Q has biochemical interests he might inquire further:
03500	       Q: What is cyanide's mechanism of drug action on the respiratory center?
03600	And so on, since there is no bottom to the questions which might be asked.
03700	Nor is there a top:
03800	       Q: Why did the man take cyanide?
03900	       E: Because he was depressed.
04000	       Q: What was he depressed about?
04100	       E: He lost his job.
04200	       Q: How did that happen?
04300	       E: The aircraft company let go most of their engineers because of the cut-back in defense contracts.
04400	Explanations are always incomplete because the top and bottom can be indefinitely
04500	extended and endless questions can be asked at each level.
04600	Just as the participants in explanatory dialogues
04700	decide what is taken to be problematic, so they also determine the termini of
04800	questions and answers. Each discipline has its characteristic stopping points.
04900	    In explanatory dialogues there exist larger and smaller constellations
05000	to refer to which are taken for granted as a nonproblematic background.
05100	Hence in considering  the function of paranoid thought `it goes without saying',
05200	that is, it transcends this particular field of function to say
05300	that a living teleonomic system as the larger constellation strives for
05400	maintenance and expansion of its life using smaller oriented, informed
05500	and constructive subprocesses. Also it goes without saying that at a lower
05600	level ion transport takes place through nerve-cell membranes. Every function
05700	of an organism can be viewed a governing a subfunction beneath and 
05800	depending on a transfunction above which calls it into play for a purpose.
05900	   Just as there are many alternative ways of describing, there are many
06000	alternative ways of explaining. An explanation is geared to some level
06100	of what the dialogue participants take to be the fundamental structures
06200	and processes under consideration. Since in psychiatry we cope with
06300	patients' problems using mainly symbolic-conceptual techniques,(it is true
06400	that one still has a choice between the pill and the knife as well as
06500	the spell), we are interested in aspects of human conduct which can be
06600	explained and understood at a symbol-processing level. Hence I shall
06700	attempt to explain paranoid conversational interactions by describing 
06800	in some detail a simulation of paranoid interview behavior , having in
06900	mind an audience of mental health professionals and the educated  in  fields
07000	of psychiatry, psychology, artificial intelligence, linguistics and philosophy.
07100	   Symbol processing explanations postulate an underlying intentionalistic
07200	structure of hypothetical functions or strategies, goal-directed symbol-processing
07300	procedures, having the power to produce and being responsible for
07400	the manifest phenomena.
07500	An algorithm composed of symbolic computational
07600	procedures converts input symbolic structures into output symbolic
07700	structures according to certain principles. The modus operandi
07800	of a symbolic model is simply the workings of an algorithm when run on
07900	a computer. At this level of explanation, to answer `why?' means to provide             
08000	an algorithm which makes explicit how things go together, how things come about, how things are organized to work.
08100	   To simulate the input-output behavior of a system using symbolic
08200	computational procedures, we construct a model which produces I/O
08300	behavior resembling that of the subject system being simulated. The
08400	resemblance is achieved through the workings of an inner postulated
08500	structure in the form of an algorithm, an organization of goal-directed
08600	symbol processing procedures which are responsible for the characteristic
08700	observable behavior at the input-output level. Since we do not know the
08800	structure of the `real' simulative mechanisms used by the mind-brain,
08900	our postulated structure stands as an imagined  theoretical analogue,
09000	a possible and plausible organization of procedures analogous to the
09100	unknown functions and serving as an attempt to explain the workings
09200	of the system under study. A simulation model is thus deeper than a
09300	pure black-box explanation because it postulates functionally equivalent
09400	strategies inside the box to account for observable patterns of I/O
09500	behavior. A simulation model constitutes an interpretive explanation
09600	in that it makes intelligible the connections between external input
09700	internal states and output by postulating intervening symbol-processing functions operating
09800	between symbolic input and symbolic output. An intelligible description
09900	of the model should make clear why and how it reacts as it does under
10000	various circumstances.
10100	    To cite a universal generalization to explain an individuals behavior
10200	is unsatisfactory to a questioner who is interested in what powers and
10300	liabilities are latent behind manifest phenomena. To say `x is nasty
10400	because x is paranoid and all paranoids are nasty' may be relevant,
10500	intelligible and correct but it does not cite a structure which can account
10600	for `nasty' behavior as a consequence of input and internal states of
10700	a system. A model explanation specifies particular antecedants and functions
10800	through which antecedants generate the phenomena. This approach to
10900	explanation assumes perceptible phenomena display the regularities and
11000	irregularities they do because of the nature of a (currently) imperceptible
11100	and inaccessible underlying structure.
11200	   When attempts are made to explain human behavior, principles in
11300	addition to those accounting for the natural order are invoked. `Nature
11400	entertains no opinions about us' said Nietsche but human natures do and
11500	therein lies a  source of complexity for human symbol-processing systems.
11600	Until the first quarter of the 20th century, natural sciences  have been guided by the Newtonian ideal
11700	of perfect process knowledge about inanimate objects whose behavior can
11800	be subsumed under lawlike generalizations. When a deviation from a law is
11900	noticed,it is the law which must be modified, since by definition physical objects do not break laws.
12000	When the planet Mercury was observed to deviate from the orbit predicted
12100	by Newtonian theory, no one accused the planet of being an intentional agent
12200	breaking the law; something was wrong with the theory.  Subsumptive explanation is the acceptable norm in physics
12300	but it is seldom satisfactory in accounting for the behavior
12400	of living intentionalistic systems. In considering the behavior of falling bodies
12500	no one nowadays follows the Aristotelian pattern of attributing an intention
12600	to fall to the object in question. But in the case of living systems, especially
12700	ourselves, our ideal explanatory practice remains Aristotelian in utilizing
12800	a concept of intention.(Aristotle was not wrong about everything).
12900	   Consider a man participating in a high-diving contest. In falling towards
13000	the water he falls at the rate of 32 feet per second per second. Viewing
13100	the man simply as a falling body, we explain his rate of fall by appealing to a physical
13200	law. Viewing the man as a human intentionalistic agent, we explain his dive as the result
13300	of an intention to dive in a cetain way in order to win the diving contest.
13400	His action (in contrast to mere movement) involves an intended following
13500	of certain conventional rules for what is judged by humans to constitute, say,
13600	a swan dive. Suppose part way down he chooses to change his position in
13700	mid-air and enter the water thumbing his nose at the judges. He cannot break
13800	the law of falling bodies but he can break the rules of diving and make a 
13900	gesture which expresses disrespect and which he believes will be interpreted
14000	as such by the onlookers. Our diver breaks a rule for diving but follows
14001	another rule which prescribes gestural action for insulting behavior.
14100	To explain the actions of diving and nose-thumbing, we
14200	would appeal, not to laws of natural order, but to an additional order, to
14300	principles of human order, superimposed on laws of natural order and which
14400	take into account (1)standards of appropriate action in certain situations
14500	and (2) the agents inner considerations of intention, belief and value about
14600	those situations which he finds compelling from his point of view.
14700	   In this type of explanation the explanandum, that which is being explained
14800	is the agent's informed actions, not simply his movements. When a human
14900	agent performs an action in a situation, we can ask:(1) is the action
15000	appropriate to that situation and if not, why did the agent believe his
15100	action to be called for.
15200	   As will be shown, symbol-processing explanations rely on concepts 
15300	of action, intention, belief, affect, preference, etc. These terms are
15400	close to the terms of ordinary language as is characteristic of  early
15500	stages of explanations. It is also important to note that such terms are commonly utilized 
15600	in describing computer algorithms in which final causes guide efficient causes. In
15700	an algorithm these ordinary terms can be explicitly defined and
15800	represented.
15900	   Psychiatry deals with the practical concerns of inappropriate action,
16000	belief, etc. on the part of a patient. His behavior may be inappropriate
16100	to the onlooker since it represents a lapse from the expected, a
16200	contravention of the human order. It may even appear this way to the 
16300	patient in monitoring and directing himself.But sometimes, as in severe cases of the paranoid mode
16400	the patient's behavior does not appear anomalous to himself. He maintains
16500	that anyone who understands his point of view, who conceptualizes
16600	situations as he does from the inside, would consider his outer behavior
16700	appropriate and justified. What he does not understand or accept is
16800	that his inner conceptualization is mistaken and represents a misinterpretation
16900	of the events of his experience.
17000	    The model to be presented in the sequel constitutes an attempt to
17100	explain some regularities and particular occurrences of conversational
17200	paranoid phenomena observable in the clinical situation of a psychiatric
17300	interview. The explanation is at the symbol-processing level of
17400	linguistically communicating agents and is cast in the form of a dialogue
17500	algorithm. Like all explanations it is only partially accurate, incomplete
17600	and does not claim to represent the only underlying organization of functions
17700	possible.
17800	
17900	                 ALGORITHMS
18000	
18100	   Theories can be presented in various forms such as natural language
18200	assertions, mathematical equations and computer programs. To date most
18300	theoretical explanations in psychiatry and psychology have consisted
18400	of natural language essays with all their well-known vagueness and
18500	ambiguities.Many of these formulations have been untestable, not because
18600	relevant observations were lacking but because it was unclear what
18700	the essay was really saying. Clarity is needed.
18800	     An alternative way of formulating psychological theories is now
18900	available in the form of an algorithm, a computer program, which has
19000	the virtue of being clear and explicit in its articulation and which
19100	can be run on a computer to test its internal consistency and coherence.  
19200	Since we do not know the `real' mind-brain algorithms,
19300	we construct a theoretical model which represents a partial
19400	paramorphic analogue. (See Harre, 1972). The analogy is at the symbol-
19500	processing level, not at the hardware level. A functional, computational
19600	or procedural equivalence is being postulated. The question then becomes
19700	one of determining the degree of the equivalence. Weak functional equivalence
19800	consists of indistinguishability at the outermost input-output level.
19900	Strong equivalence means correspondence at each inner I/O level, that is
20000	there exists a match not only between what is being done but how it is
20100	being done at a given level of operations.(These points will be discussed
20200	in greater detail in Chapter 3).
20300	   An algorithm represents an organization of procedures or functions
20400	which represents an `effective procedure'. It is essential for the reader to grasp this concept.
20500	An effective procedure consists of two ingredients:
20600	       (1) A programming language in which procedural rules of behavior
20700	          can be rigorously and unambiguously specified.
20800	     (2) A machine processor which can rapidly and reliably carry out
20900	          the processes specified by the procedural rules.
21000	The specifications of (1), written in a formally defined programming
21100	language, is termed an algorithm or program while (2) involves a computer
21200	as the machine processor, a set of deterministic physical mechanisms
21300	which can perform the operations specified in the algorithm. The
21400	algorithm is called `effective' because it actually works, performing
21500	as intended when run on the machine processor.
21600	     It is worth remphasizing that a simulation model postulates
21700	procedures analogous to the real and unknown procedures. The analogy being 
21800	drawn here is between specified processes and their generating systems.
21900	Thus
22000	
22100	      mental process    computational process
22200	      --------------:: ----------------------
22300	    brain hardware      computer hardware and
22400	    and programs           programs
22500	The analogy is not simply between computer hardware and brain wetware.
22600	We are not comparing the structure of neurons with the structure of
22700	transisitors; we are comparing the organization of symbol-processing
22800	procedures in an algorithm with symbol-processing procedures of the
22900	mind-brain. The central nervous system contains a representation of
23000	the experience of its holder. A model builder has a conceptual representation
23100	of that representation which he demonstrates in the form of an algorithm.
23200	Thus an algorithm is a demonstration of a  representation of a representation.
23300	    When an algorithm runs on a computer the postulated explanatory
23400	structure becomes actualized, not described. (To describe the model
23500	is to present , among other things, its embodied theory). A simulation model such as the
23600	one presented here can be interacted with by a person at the linguistic
23700	level as a communicating agent in the world. Its communicative behavior
23800	can be experienced in a concrete form by a human observer-actor.
23900	Thus it can be known by acquaintance, by first-hand knowledge, as well
24000	as by the second-hand knowledge of description.
24100	   Since the algoritm is written in a programming language, it is hermetic
24200	and opaque except to a few people, who in general do not enjoy reading
24300	other people's code. Hence the intelligibility requirement for explanations
24400	must be met in other ways. In an attempt to open the model to scrutiny
24500	I shall describe the model in detail using diagrams and interview
24600	examples profusely.