In 1957, the Artificial Intelligence Project was started at MIT. Two young assistant Professors, Marvin Minsky and John McCarthy launched this bold venture after the successful summer conference at Dartmouth in 1956. In that same environment were Warren McCullough, developing ideas about neural nets, Jerry Lettvin, exploring how frogs eyes and brains worked, Norbert Weiner looking at cybernetic models of machine and human behavior, and Noam Chomsky, developing formal models of language competence. Meanwhile, at what is now Carnegie Mellon University, Allen Newell and Herbert Simon were exploring Complex Information Processing-building models of human problem solving. In those first heady years, Artificial Intelligence showed promise in automating mathematical activity, understanding language, using logic to solve problems, modeling human intelligence in an analogical reasoning task, planning, and learning. Back then we thought, if only machines were a little bigger, and we had just one or two more ideas, we could develop theories and prototypes of intelligence that would both inform us about how humans work, and be our partners in solving hard problems.
The bad news is that we were over-optimistic. The scale and difficulty of the problems were not apparent to us then (and may still not be now). The good news is that we have made tremendous strides both in our understanding of the theory, and in applying those theories to real problems. IJCAI-97 took place August 23-29, 1997 in Nagoya. A highlight of that conference was an impressive series of invited lectures that provided excellent examples of how far the field of Artificial Intelligence has progressed, stories of some major accomplishments and its major challenges. We decided to invite each of these speakers to submit a paper on the sub.ject of their talk to a special issue of the journal, providing them the space and the time to expand on their subject. The result is this sterling collection of papers. In continuity with those initial efforts, they show how AI has evolved to deal with problems of automating mathematics, understanding and using natural language, using logic to solve problems, planning, and learning.
The first set of papers provide a look at how Artificial Intelligence is being used in "applications", problems embedded in and defined by a real world environment. These