In AI we talk about expert systems.

This is the second of two papers about MOLGEN.

A given representational language can be implemented in all manner of ways: predicate calculus assertions may be implemented as lists, as character sequences, Minsky introduced the terminology of'frames' to unify and denote a loose as trees, as networks, as patterns in an associative memory, etc: collection of related ideas on knowledge representation: a collection which, all giving different computational properties but all encoding the same representational since the publication of his paper (Minsky, 1975) has become even looser.

The next step is to find an algorithm for finding paths in P2, then apply this al!drithin in a certain way as a heuristic Many combinatorially large problems cannot be solved for P1. As an elementary example, the rectilinear distance feasibly by exhaustive case analysis or brute force function is an efficient heuristic for finding paths in a search, but can be solved efficiently if a heuristic can be "Manhattan street pattern" graph even when some (but devised to guide the search. Finding such a heuristic for not too many) of the streets have been blockaded (i.e., a given problem, however, usually requires an exercise of some edges are removed from the. graph).

"Almost all the basic methods used by

In this paper we present a new algorithm for searching trees. The algorithm, which we have named For this reason, the search is usually limited in some way (e.g., number of nodes B*, finds a proof that an arc at the root of a search tree is better than any other. It does this by to be expanded, or maximum depth to which it may go).

Human programmers seem to know a lot about programming. This suggests a way to try to build here was designed to shed some light on questions like these.

Marvin Lee Minsky was born in New York on 9th August, 1927. He received his B.A from Harvard in 1950 and Ph.D in Mathematics from Princeton in 1954. For the next three years he was a member of the Harvard University Society of Fellows, and in 1957-58 was staff member of the M.I.T. Lincoln Laboratories. At present he is Assistant Professor of Mathematics at M.I.T. where he is giving a course in Automata and Artificial Intelligence and is also staff member of the Research Laboratory of Electronics. SUMMARY THIS paper is an attempt to discuss and partially organize a number of ideas concerning the design or programming of machines to work on problems for which the designer does not have, in advance, practical methods of solution. Particular attention is given to processes involving pattern recognition, learning, planning ahead, and the use of analogies or?models!. Also considered is the question of designing "administrative" procedures to manage the use of these other devices.

If ability to perform complex calculations were a sufficient criterion, then even a conventional digital computor could lay claim to more intelligence than any of usand perhaps we had better let it make away with the word and be done with it.

The next project was Joel Moses's program SIN. See Moses, Symbolic Integration: The Stormy Decade, 14 Comm.