Linear Logical Algorithms, Robert J. Simmons and Frank Pfenning, 2008.

Bottom-up logic programming can be used to declaratively specify many algorithms in a succinct and natural way, and McAllester and Ganzinger have shown that it is possible to define a cost semantics that enables reasoning about the running time of algorithms written as inference rules. Previous work with the programming language Lollimon demonstrates the expressive power of logic programming with linear logic in describing algorithms that have imperative elements or that must repeatedly make mutually exclusive choices. In this paper, we identify a bottom-up logic programming language based on linear logic that is amenable to efficient execution and describe a novel cost semantics that can be used for complexity analysis of algorithms expressed in linear logic.

In my last post, I linked to a paper by Ganzinger and McAllester about specifying algorithms as logic programs, and a) admired how concise and natural the programs were, and b) was sad that the logic programs used some "non-logical" operations, such as deletion.

So, what does it mean for an operation to be "non-logical", and why is it a bad thing? Roughly speaking, you can think of the analogy: non-logical operations are to logic programs what impure operations are to functional programs -- they are features which break some parts of the equational theory of the language. Now, the Curry-Howard correspondence for functional programs says that types are propositions, and programs are proofs. It turns out that a different version of this correspondence holds for logic programs: in logic programming, a set of propositions is a program, and the execution of a program corresponds to a process of proof search -- you get a success when execution finds a proof of the goal.

When you have nonlogical operations in your logic programming language, you've introduced operators that don't correspond to valid rules of inference, so even if your logic program succeeds, the success might not correspond to a real proof. Deletion of facts from a database is a good example of a nonlogical operation. Regular intuitionistic and classical logic is monotonic: deduction from premises can only learn new facts, it can never disprove things you already knew to be true. Since deletion removes facts from the set of things you know, it can't have a logical interpretation in classical/intuitionistic logic.

However, it turns out that not all logics are monotonic, and in this paper Simmons and Pfenning show that if you take the language of propositions to be a fragment of linear logic, then all of the operations that Ganzinger and McAllester use actually do have a nice logical interpretation.