On Solving the Qualification Problem

The qualification problem may be the most fundamental difficulty in formalizing common sense knowledge in general, and in formalizing knowledge about action in particular. This position paper argues that the qualification problem is intrinsicallycomputational as opposed to representational. This does not imply that explicit, formal, knowledge has no role in the production of commonsensical behaviour, but it does imply that the qualification problem cannot be solved using currently available representation formalisms. For a future representation formalism to help in solving the qualification problem, it will be vital for it to possess a context mechanism. Artificial intelligence research has a history of wishful thinking. In the 1950s the hope was that the right heuristic search algorithms, if only they could be found, would suffice to explain and duplicate human problem-solving skills. Another hope arose after it became clear that large quantities of initial knowledge were necessary in problem-solving: that this knowledge could be acquired by a natural language understanding program which could be written after relatively simple principles of syntax and semantics were elucidated. Neither of these hopes has been realized, but wishful thinking springs eternal, and many researchers still hope that it is possible somehow to obtain the benefits of possessing a large mass of common sense knowledge without actually stating all the knowledge formally.1 Lenat and Guha call attempts of this nature “free lunch tries” [Lenat and Guha, 1990]. In the knowledge representation community we are justifiably skeptical of the free lunch tries of others, but we are still lured by a hope of our own. This is the hope that the right nonmonotonic logic can, in and by itself, solve dilemmas of common sense reasoning. The two bestknown examples of the inferences that nonmonotonic logics are supposed to sanction concern a canary and a turkey: “Tweety is a bird; therefore Tweety can fly.” “Loading then shooting kills Fred; therefore loading, then waiting, then shooting kills Fred.” “The fundamental issues of AI can only be solved with an orchestrated application of fuzzy logic, neural networks, genetic algorithms, and probabilistic reasoning.” [Vadiee and Jamshidi, 1994] The desire for a formalism where these inferences are legitimate is the desire for a formalism where appropriate conclusions can be drawn even in the absence of full knowledge of all relevant circumstances. The qualification problem, as commonly understood, is that in almost all common sense scenarios, it is impossible to state all relevant circumstances. In other words, general rules of common sense are always incomplete.2 However many preconditions have been taken into account in the formalization of a rule, one can think of further preconditions whose truth influences the truth of the consequent of the rule, so the formalization should mention even more antecedents. The first example of nonmonotonic reasoning above illustrates this phenomenon. The general rule that birds fly in actuality has many unstated further antecedents, such as that the birds in question are not penguins. The second example of nonmonotonic reasoning above is commonly viewed as illustrating the frame problem, but the frame problem can be viewed as a version of the qualification problem: here for example, loading then shooting only kills Fred if many other unstated assumptions are true. In a nutshell, the frame problem is that one only wants to state the conditions under which a property of the world does not persist, leaving the conditions under which it does persist unstated. We can distinguish weak and strong variants of the qualification problem. The weak form is the case where the unstated additional relevant antecedents could in principle be made explicit, while the strong form is the case where these antecedents could not plausibly be enumerated even in principle. An instance of the frame problem is an instance of the weak qualification problem if the conditions under which world properties persist can in principle be enumerated; if they cannot, one has an instance of the strong qualification problem. The conventional intuition behind the search for a nonmonotonic logic as a solution to the qualification problem is that rules of common sense express “default” truths. According to this intuition, the rule that “if you turn the key, the car starts”, which ignores further preconditions that the battery should not be dead, the fuel pump should not be clogged, the gas should contain no sugar, and so on, should be formalized along the following lines: This general rule itself is also incomplete. Some rules of common sense are definitional and therefore can be specified completely. From: AAAI Technical Report SS-95-07. Compilation copyright © 1995, AAAI (www.aaai.org). All rights reserved. defaultrule129: turn-key -> car-starts dead-battery cancels default129 clogged-fuel cancels default129 sugar-in-gas cancels default129