Forward Chaining Logic Programming with the ATMS

Book One

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 6

AI Architectures

Two powerful reasoning tools have recently appeared, logic programming and assumption-based truth maintenance systems (ATMS). An ATMS offers significant advantages to a problem solver: assumptions are easily managed and the search for solutions can be carried out in the most general context first and in any order. Logic programming allows us to program a problem solver declaratively-describe what the problem is, rather than describe how to solve the problem. However, we are currently limited when using an ATMS with our problem solvers, because we are forced to describe the problem in terms of a simple language of forward implications. In this paper we present a logic programming language, called FORLOG, that raises the level of programming the ATMS to that of a powerful logic programming language. FORLOG supports the use of "logical variables" and both forward and backward reasoning. FORLOG programs are compiled into a data-flow language (similar to the RETE network) that efficiently implements deKleer’s consumer architecture. FORLOG has been implemented in Interlisp-D.