jbn@GLACIER.STANFORD.EDU (John B. Nagle) (02/29/88)
McCarthy has recently described two paths to artificial intelligence. But his two, while the most active, are not the only ones in which substantial work is underway. A more general taxonomy might be outlined as follows. 1. "Good, old fashioned AI". This is the line of development that includes LISP, GPS, the Blocks World, automatic theorem proving, and expert systems. The major thrust of this line of work is to model the world using formalisms related to mathematical logic. 2. Neural networks. This line begins with perceptrons and continues through neural networks to connectionism. The major thrust of this line is the development of massively parallel self-organizing systems. 3. Engineered artificial life. This bottom-up approach begins with such efforts as the Hopkins Beast, continues through the early MIT eye-hand coordination work, and continues today with Brooks' artificial insects and much of Moravec's robotics work. The major thrust here is the construction of robots that function in the real world, using whatever technology seems appropriate. 4. Study and replication of the detailed structure of biological intelligence, without necessarily understanding how it works. Drexler proposes this approach, which is primarily in the discussion phase at this point. It is important not to confuse #2 and #4. John Nagle
tjhorton@ai.toronto.EDU ("Timothy J. Horton") (03/07/88)
jbn@GLACIER.STANFORD.EDU (John B. Nagle) writes (very roughly): > McCarthy has recently described two paths to artificial intelligence. >But his two, while the most active, are not the only ones in which substantial >work is underway. A more general taxonomy might be outlined as follows: > 1. "Good, old fashioned AI". ... to model the world using formalisms > related to mathematical logic. > 2. Neural networks. ... development of massively parallel > self-organizing systems. > 3. Engineered artificial life. (bottom-up approach) ... construction > of robots that function in the real world, using whatever technology > seems appropriate. > 4. Study and replication of the detailed structure of biological > intelligence, without necessarily understanding how it works. Could anyone fill out this tree a little more? For instance, what about Woods' work on abstract procedures (not to be confused with proceduralism)? He wants something more general than logic -- not throwing it out, but not accepting it as sufficient or appropriate for the whole job. What about anything else? Surely there are "mathematical" theoreticians that hope for something more than logic, that ought to be included here? The latest issue of "Computational Intelligence" had more than a score of responses to Drew McDermott's critique of pure logicism, and one heck of a lot of camps got staked out in the process.