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  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 we  still also have  the pill and the knife),
06500	we are interested in aspects of human conduct which can be
06600	explained, understood, and modified 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 colleagues   in  fields
07000	of psychiatry, psychology, artificial intelligence, linguistics and philosophy.
07100	   Symbol processing explanations postulate an underlying intentionalistic
07200	structure of hypothetical mechanisms, functions or strategies, goal-directed symbol-processing
07300	procedures, having the power to produce and being responsible for
07400	the manifest phenomena. In this ethogenic (generating behavior, Harre[ ]) approach the term "mechanism"
07500	is not used in the strict classical mechanical sense of particles obeying laws of
07600	motion. Instead it is used in the more general sense of modus operandi as
07700	in the mechanism for electing a president or the mechanism of evolutionary
07800	change. Thus I shall avoid the terms "mechanical" and "mechanistic" in order
07900	to avoid metaphors and images of Newtonian physics. As will become clear,
08000	this ethogenic viewpoint uses the terms "mechanisms", "functions", "procedures"
08100	and "strategies" as roughly synonoymous.
08200	
08300	
08400	An algorithm composed of symbolic computational
08500	procedures converts input symbolic structures into output symbolic
08600	structures according to certain principles. The modus operandi
08700	of a symbolic model is simply the workings of an algorithm when run on
08800	a computer. At this level of explanation, to answer `why?' means to provide             
08900	an algorithm which makes explicit how symbolic structures go together,
09000	how they are organized to work to generate patterns of manifest phenomena.
09001	
09100	   To simulate the input-output behavior of a system using symbolic
09200	computational procedures, we construct a model which produces I/O
09300	behavior resembling that of the subject system being simulated. The
09400	resemblance is achieved through the workings of an inner postulated
09500	structure in the form of an algorithm, an organization of intentionalistic
09600	symbol processing procedures which are responsible for the characteristic
09700	observable behavior at the input-output level. Since we do not know the
09800	structure of the `real' simulative mechanisms used by the mind-brain,
09900	our postulated structure stands as an imagined  theoretical analogue,
10000	a possible and plausible organization of mechanisms analogous to the
10100	unknown mechanisms and serving as an attempt to explain the workings
10200	of the system under study. A simulation model is thus deeper than a
10300	pure black-box explanation because it postulates functionally equivalent
10400	mechanisms inside the box to account for observable patterns of I/O
10500	behavior. A simulation model constitutes an interpretive explanation
10600	in that it makes intelligible the connections between external input
10700	internal states and output by postulating intervening symbol-processing procedures operating
10800	between symbolic input and symbolic output. An intelligible description
10900	of the model should make clear why and how it reacts as it does under
11000	various circumstances.
11100	    To cite a universal generalization to explain an individuals behavior
11200	is unsatisfactory to a questioner who is interested in what powers and
11300	liabilities are latent behind manifest phenomena. To say `x is nasty
11400	because x is paranoid and all paranoids are nasty' may be relevant,
11500	intelligible and correct but it does not cite a structure which can account
11600	for `nasty' behavior as a consequence of input and internal states of
11700	a system. A model explanation specifies particular antecedants and mechanisms
11800	through which antecedants generate the phenomena. This ethogenic approach to
11900	explanation assumes perceptible phenomena display the regularities and
12000	irregularities they do because of the nature of a (currently) imperceptible
12100	and inaccessible underlying structure.
12200	   When attempts are made to explain human behavior, principles in
12300	addition to those accounting for the natural order are invoked. `Nature
12400	entertains no opinions about us' said Nietsche but human natures do and
12500	therein lies a  source of complexity for the understanding of human nature.
12600	Until the first quarter of the 20th century, natural sciences  have been guided by the Newtonian ideal
12700	of perfect process knowledge about inanimate objects whose behavior can
12800	be subsumed under lawlike generalizations. When a deviation from a law was
12900	noticed,it was the law which was modified, since by definition physical objects do not have the power to break laws.
13000	When the planet Mercury was observed to deviate from the orbit predicted
13100	by Newtonian theory, no one accused the planet of being an intentional agent
13200	breaking the law; something was wrong with the theory.  Subsumptive explanation is the acceptable norm in physics
13300	but it is seldom satisfactory in accounting for the behavior
13400	of living intentionalistic systems. In considering the behavior of falling bodies
13500	no one nowadays follows the Aristotelian pattern of attributing an intention
13600	to fall to the object in question. But in the case of living systems, especially
13700	ourselves, our ideal explanatory practice remains Aristotelian in utilizing
13800	a concept of intention.(Aristotle was not wrong about everything).
13900	   Consider a man participating in a high-diving contest. In falling towards
14000	the water he falls at the rate of 32 feet per second per second. Viewing
14100	the man simply as a falling body, we explain his rate of fall by appealing to a physical
14200	law. Viewing the man as a human intentionalistic agent, we explain his dive as the result
14300	of an intention to dive in a cetain way in order to win the diving contest.
14400	His action (in contrast to mere movement) involves an intended following
14500	of certain conventional rules for what is judged by humans to constitute, say,
14600	a swan dive. Suppose part way down he chooses to change his position in
14700	mid-air and enter the water thumbing his nose at the judges. He cannot break
14800	the law of falling bodies but he can break the rules of diving and make a 
14900	gesture which expresses disrespect and which he believes will be interpreted
15000	as such by the onlookers. Our diver breaks a rule for diving but follows
15100	another rule which prescribes gestural action for insulting behavior.
15200	To explain the actions of diving and nose-thumbing, we
15300	would appeal, not to laws of natural order, but to an additional order, to
15400	principles of human order, superimposed on laws of natural order and which
15500	take into account (1)standards of appropriate action in certain situations
15600	and (2) the agents inner considerations of intention, belief and value 
15700	which he finds compelling from his point of view.
15800	   In this type of explanation the explanandum, that which is being explained
15900	is the agent's informed actions, not simply his movements. When a human
16000	agent performs an action in a situation, we can ask:(1) is the action
16100	appropriate to that situation and if not, why did the agent believe his
16200	action to be called for.
16300	   As will be shown, symbol-processing explanations rely on concepts 
16400	of action, intention, belief, affect, preference, etc. These terms are
16500	close to the terms of ordinary language as is characteristic of  early
16600	stages of explanations. It is also important to note that such terms are commonly utilized 
16700	in describing computer algorithms in which final causes guide efficient causes. In
16800	an algorithm these ordinary terms can be explicitly defined and
16900	represented.
17000	   Psychiatry deals with the practical concerns of inappropriate action,
17100	belief, etc. on the part of a patient. His behavior may be inappropriate
17200	to the onlooker since it represents a lapse from the expected, a
17300	contravention of the human order. It may even appear this way to the 
17400	patient in monitoring and directing himself.But sometimes, as in severe cases of the paranoid mode
17500	the patient's behavior does not appear anomalous to himself. He maintains
17600	that anyone who understands his point of view, who conceptualizes
17700	situations as he does from the inside, would consider his outer behavior
17800	appropriate and justified. What he does not understand or accept is
17900	that his inner conceptualization is mistaken and represents a misinterpretation
18000	of the events of his experience.
18100	    The model to be presented in the sequel constitutes an attempt to
18200	explain some regularities and particular occurrences of conversational
18300	paranoid phenomena observable in the clinical situation of a psychiatric
18400	interview. The explanation is at the symbol-processing level of
18500	linguistically communicating agents and is cast in the form of a dialogue
18600	algorithm. Like all explanations it is only partially accurate, incomplete
18700	and does not claim to represent the only conceivable structure of mechanisms.
18800	
18900	                 ALGORITHMS
19000	
19100	   Theories can be presented in various forms such as natural language
19200	assertions, mathematical equations and computer programs. To date most
19300	theoretical explanations in psychiatry and psychology have consisted
19400	of natural language essays with all their well-known vagueness and
19500	ambiguities.Many of these formulations have been untestable, not because
19600	relevant observations were lacking but because it was unclear what
19700	the essay was really saying. Clarity is needed.
19800	     An alternative way of formulating psychological theories is now
19900	available in the form of ethogenic algorithms, computer programs, which have
20000	the virtue of being clear and explicit in their articulation and which
20100	can be run on a computer to test internal consistency and external correspondence with the data of observation.
20200	Since we do not know the `real' mind-brain algorithms,
20300	we construct a theoretical model which represents a partial
20400	paramorphic analogue. (See Harre, 1972). The analogy is at the symbol-
20500	processing level, not at the hardware level. A functional, computational
20600	or procedural equivalence is being postulated. The question then becomes
20700	one of determining the degree of the equivalence. Weak functional equivalence
20800	consists of indistinguishability at the outermost input-output level.
20900	Strong equivalence means correspondence at each inner I/O level, that is
21000	there exists a match not only between what is being done but how it is
21100	being done at a given level of operations.(These points will be discussed
21200	in greater detail in Chapter 3).
21300	   An algorithm represents an organization of symbol-processing mechanisms or functions
21400	which represent an `effective procedure'. It is essential here to grasp this concept.
21500	An effective procedure consists of two ingredients:
21600	       (1) A programming language in which procedural rules of behavior
21700	          can be rigorously and unambiguously specified.
21800	     (2) A machine processor which can rapidly and reliably carry out
21900	          the processes specified by the procedural rules.
22000	The specifications of (1), written in a formally defined programming
22100	language, is termed an algorithm or program while (2) involves a computer
22200	as the machine processor, a set of deterministic physical mechanisms
22300	which can perform the operations specified in the algorithm. The
22400	algorithm is called `effective' because it actually works, performing
22500	as intended when run on the machine processor.
22600	     It is worth remphasizing that a simulation model postulates
22700	procedures analogous to the real and unknown procedures. The analogy being 
22800	drawn here is between specified processes and their generating systems.
22900	Thus
23000	
23100	      mental process    computational process
23200	      --------------:: ----------------------
23300	    brain hardware      computer hardware and
23400	    and programs           programs
23500	The analogy is not simply between computer hardware and brain wetware.
23600	We are not comparing the structure of neurons with the structure of
23700	transisitors; we are comparing the organization of symbol-processing
23800	procedures in an algorithm with symbol-processing procedures of the
23900	mind-brain. The central nervous system contains a representation of
24000	the experience of its holder. A model builder has a conceptual representation
24100	of that representation which he demonstrates in the form of an algorithm.
24200	Thus an algorithm is a demonstration of a  representation of a representation.
24300	    When an algorithm runs on a computer the postulated explanatory
24400	structure becomes actualized, not described. (To describe the model
24500	is to present , among other things, its embodied theory). A simulation model such as the
24600	one presented here can be interacted with by a person at the linguistic
24700	level as a communicating agent in the world. Its symbolic communicative behavior
24800	can be experienced in a concrete form by a human observer-actor.
24900	Thus it can be known by acquaintance, by first-hand knowledge, as well
25000	as by the second-hand knowledge of description.
25100	   Since the algoritm is written in a programming language, it is hermetic
25200	and opaque except to a few people, who in general do not enjoy reading
25300	other people's code. Hence the intelligibility requirement for explanations
25400	must be met in other ways. In an attempt to open the model to scrutiny
25500	I shall describe the model in detail using diagrams and interview
25600	examples profusely.