MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB
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Regularities in the world give rise to regularities in the way in which we deal with the world. That is to say, we fall into routines. THe author has been studying the phenomena of routinization, the process by which institutionalized patterns of interaction with the world arise and evolve in everyday life. Underlying this evolution is a dialectical process of internalization First you build a model of some previously unarticulated emergent aspect of an existing routine. Armed with an incrementally more global view of the interaction, you can often formulate an incrementally better informed plan of attack. A routine is not a plan in the sense of the classical planning literature, except in the theoretical limit of this process. The author is implementing this theory using running arguments, a technique for writing rule-based programs for intelligent agents. Because a running argument is compiled into TMS networks as it proceeds, incremental changes in the world require only incremental recomputation of the reasoning about what actions to take next. The system supports a style of programming, dialectical argumentation, that has many important properties that recommend it as a substrate for large AI systems. One of these might be called additivity an agent can modify its reasoning in a class of situations by adducing arguments as to why its previous arguments were incorrect in those cases. Keywords LISP programming language.
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