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=====4.1.3.1. Inquiry and Computation=====
=====4.1.3.1. Inquiry and Computation=====
Three questions immediately arise in the connection between inquiry and computation. As they reflect on the concept of inquiry, these questions have to do with its integrity, its effectiveness, and its complexity.
# Integrity. Do all the activities and all the processes that are commonly dubbed "inquiry" have anything essential in common?
# Effectiveness. Can any useful parts of these so called inquiries be automated in practice?
# Complexity. Just how deep is the analysis, the disassembly, or the "takedown" of inquiry that is required to reach the level of routine steps?
The issues of effectiveness and complexity are discussed throughout the remainder of this text, but the problem of integrity must be dealt with immediately, since doubts about it can interfere with the very ability to use the word "inquiry" in this discussion.
Thus, I must examine the integrity, or well-definedness, of the very idea of inquiry, in other words, "inquiry" as a general concept rather than a catch all term. Is the faculty of inquiry a principled capacity, leading to a disciplined form of conduct, or is it only a disjointed collection of unrelated skills? As it is currently carried out on computers, inquiry includes everything from database searches, through dynamic simulation and statistical reasoning, to mathematical theorem proving. Insofar as these tasks constitute specialized efforts, each one needs software that is tailored to the individual purpose. To the extent that these different modes of investigation contribute to larger inquiries, present methods for coordinating their separate findings are mostly ad hoc and still a matter of human skill. Thus, one can question whether the very name "inquiry" succeeds in referring to a coherent and independent process.
Do all the varieties of inquiry have something in common, a structure or a function that defines the essence of inquiry itself? I will say "yes". One advantage of this answer is that it brings the topic of inquiry within human scope, and also within my capacity to research. Without this, the field of inquiry would be impossible for any one human being to survey, because a person would have to cover the union of all the areas that employ inquiry. By grasping what is shared by all inquiries, I can focus on the intersection of their generating principles. Another benefit of this alternative is that it promises a common medium for inquiry, one in which the many disparate pieces of our puzzling nature may be bound together in a unified whole.
When I look at other examples of instruments that people have used to extend their capacities, I see that two questions must be faced. First, what are the principles that enable human performance? Second, what are the principles that can be augmented by available technology? I will refer to these two issues as the question of original principles and the question of technical extensions, respectively. Following this model leads me to examine the human capacity for inquiry, asking which of its principles can be reflected in the computational medium, and which of its faculties can be sharpened in the process. It is not likely that everybody with the same interests and applications would answer these questions the same way, but I will describe how I approach them, what has resulted so far, and what directions I plan to explore next.
The focus of my work will narrow in three steps. First, I will concentrate on the design of intelligent software systems that support inquiry. Then, I will select mathematical systems theory as an indispensable tool, both for the analysis of inquiry itself and for the design of programs to support it. Finally, I will develop a theory of qualitative differential equations, implement methods for their computation and solution, and apply the resulting body of techniques to two kinds of recalcitrant problems, (1) those where an inquiry must begin with too little information to justify quantitative methods, and (2) those where a complete logical analysis is necessary to identify critical assumptions.
=====4.1.3.2. Inquiry Driven Systems=====
=====4.1.3.2. Inquiry Driven Systems=====
