The goal of this paper is to lay a logical foundation for discourse theories by providing analgebraic foundation of compositional formalisms for discourse semantics as an analogon tothe simply typed (lambda)-calculus. Just as that can be specialized to type theory by simply providinga special type for truth values and postulating the quantifiers and connectives as constantswith fixed semantics, the proposed dynamic (lambda)-calculus DLC can be specialized to (lambda)-DRT byessentially the same measures, yielding a much more principled and modular treatment of(lambda)-DRT than before; DLC is also expected to eventually provide a conceptually simple basisfor studying higher-order unification for compositional discourse theories.Over the past few years, there have been a series of attempts [Zee89, GS90, EK95, Mus96,KKP96, Kus96] to combine the Montagovian type theoretic framework [Mon74] with dynamicapproaches, such as DRT [Kam81]. The motivation for these developments is to obtain a generallogical framework for discourse semantics that combines compositionality and dynamic binding.Let us look at an example of compositional semantics construction in (lambda)-DRT which is one ofthe above formalisms [KKP96, Kus96]. By the use of fi-reduction we arrive at a first-order DRTrepresentation of the sentence A i man sleeps. (i denoting an index for anaphoric binding.)
This paper shows how a new approach to theorem provingby analogy is applicable to real maths problems. This approach worksat the level of proof-plans and employs reformulation that goes beyondsymbol mapping. The Heine-Borel theorem is a widely known result inmathematics. It is usually stated in R 1 and similar versions are also truein R 2 , in topology, and metric spaces. Its analogical transfer was proposedas a challenge example and could not be solved by previous approachesto theorem proving by analogy. We use a proof-plan of the Heine-Boreltheorem in R 1 as a guide in automatically producing a proof-plan of theHeine-Borel theorem in R 2 by analogy-driven proof-plan construction.
This paper addresses a model of analogy-driven theorem proving that is more general and cognitively more adequate than previous approaches. The model works at the level ofproof-plans. More precisely, we consider analogy as a control strategy in proof planning that employs a source proof-plan to guide the construction of a proof-plan for the target problem. Our approach includes a reformulation of the source proof-plan. This is in accordance with the well known fact that constructing ananalogy in maths often amounts to first finding the appropriate representation which brings out the similarity of two problems, i.e., finding the right concepts and the right level of abstraction. Several well known theorems were processed by our analogy-driven proof-plan construction that could not be proven analogically by previous approaches.
This paper addresses analogy-driven auto-mated theorem proving that employs a sourceproof-plan to guide the search for a proof-planof the target problem. The approach presen-ted uses reformulations that go beyond symbolmappings and that incorporate frequently usedre-representations and abstractions. Severalrealistic math examples were successfully pro-cessed by our analogy-driven proof-plan con-struction. One challenge example, a Heine-Borel theorem, is discussed here. For this ex-ample the reformulaitons are shown step bystep and the modifying actions are demon-strated.
CL A M is a proof planner, developed by the Dream group in Edinburgh,that mainly operates for inductive proofs. This paper addresses the questionhow an analogy model that I developed independently of CL A M can beapplied to CL A M and it presents analogy-driven proof plan construction as acontrol strategy of CL A M . This strategy is realized as a derivational analogythat includes the reformulation of proof plans. The analogical replay checkswhether the reformulated justifications of the source plan methods hold inthe target as a permission to transfer the method to the target plan. SinceCL A M has very efficient heuristic search strategies, the main purpose ofthe analogy is to suggest lemmas, to replay not commonly loaded methods,to suggest induction variables and induction terms, and to override controlrather than to construct a target proof plan that can be built by CL A Mitself more efficiently.
Distributed systems are an alternative to shared-memorymultiprocessors for the execution of parallel applications.PANDA is a runtime system which provides architecturalsupport for efficient parallel and distributed program-ming. PANDA supplies means for fast user-level threads,and for a transparent and coordinated sharing of objectsacross a homogeneous network. The paper motivates themajor architectural choices that guided our design. Theproblem of sharing data in a distributed environment isdiscussed, and the performance of appropriate mecha-nisms provided by the PANDA prototype implementation isassessed.