This paper describes a uniform formalization of much of the current work in artificial intelligence on inference systems. We show that many of these systems, including first-order theorem provers, assumption-based truth maintenance systems (ATMSS), and unimplemented formal systems such as default logic or circumscription, can be subsumed under a single general framework.We begin by defining this framework, which is based on a mathematical structure known as a bilattice. We present a formal definition of inference using this structure and show that this definition generalizes work involving ATMSS and some simple nonmonotonic logics.Following the theoretical description, we describe a constructive approach to inference in this setting; the resulting generalization of both conventional inference and ATMSS is achieved without incurring any substantial computational overhead. We show that our approach can also be used to implement a default reasoner, and discuss a combination of default and ATMS methods that enables us to formally describe an "incremental" default reasoning system. This incremental system does not need to perform consistency checks before drawing tentative conclusions, but can instead adjust its beliefs when a default premise or conclusion is overturned in the face of convincing contradictory evidence. The system is therefore much more computationally viable than earlier approaches.Finally, we discuss the implementation of our ideas. We begin by considering general issues that need to be addressed when implementing a multivalued approach such as that we are proposing, and then turn to specific examples showing the results of an existing implementation. This single implementation is used to solve a digital simulation task using first-order logic, a diagnostic task using ATMSS as suggested by de Kleer and Williams, a problem in default reasoning as in Reiter's default logic or McCarthy's circumscription, and to solve the same problem more efficiently by combining default methods with justification information. All of these applications use the same general-purpose bilattice theorem prover and differ only in the choice of bilattice being considered.Le prksent article dkcrit la formalisation uniforme d'une grande partie du travail courant dans le domain des systkmes d'infkrence. L'article montre que bon nombre de ces systkmes, dont les dkmonstrateurs de thkorkme de premier ordre, les systkmes de vCritks logiques bakes sur des hypothkses (ATMS) et les systkmes formels qui ne sont pas mis en oeuvre, telle la logique implicite et la circonscription, peuvent &tre subsumes dans un seul cadre general.Nous commenqons par dkfinir ce cadre, qui est bas6 sur une structure mathematique appelCe treillis bidimensionnel. Nous donnons ensuite une definition formelle de l'infkrence en utilisant cette structure, et montrons que cette definition gknknlise le travail mettant, en jeu les ATMS et une certaine forrne de logique non monotone.Nous poursuivons, aprks cette description thtorique, par la prksentation d'une approche...

Because of their occasional need to return to shallow points in a search tree, existing backtracking methods can sometimes erase meaningful progress toward solving a search problem. In this paper, we present a method by which backtrack points can be moved deeper in the search space, thereby avoiding this di culty. The technique developed is a variant of dependency-directed backtracking that uses only polynomial space while still providing useful control information and retaining the completeness guarantees provided by earlier approaches.

No abstract

BACKGROUND AND OBJECTIVES: Historically, autosomal recessive 5q-linked spinal muscular atrophy (SMA) has been the leading inherited cause of infant death. SMA is caused by the absence of the SMN1 gene, and SMN1 gene replacement therapy, onasemnogene abeparvovec-xioi, was Food and Drug Administration approved in May 2019. Approval included all children with SMA age ,2 years without end-stage weakness. However, gene transfer with onasemnogene abeparvovec-xioi has been only studied in children age #8 months. METHODS:In this article, we report key safety and early outcome data from the first 21 children (age 1-23 months) treated in the state of Ohio.RESULTS: In children #6 months, gene transfer was well tolerated. In this young group, serum transaminase (aspartate aminotransferase and alanine aminotransferase) elevations were modest and not associated with g glutamyl transpeptidase elevations. Initial prednisolone administration matched that given in the clinical trials. In older children, elevations in aspartate aminotransferase, alanine aminotransferase and g glutamyl transpeptidase were more common and required a higher dose of prednisolone, but all were without clinical symptoms. Nineteen of 21 (90%) children experienced an asymptomatic drop in platelets in the first week after treatment that recovered without intervention. Of the 19 children with repeated outcome assessments, 11% (n = 2) experienced stabilization and 89% (n = 17) experienced improvement in motor function. CONCLUSIONS:In this population, with thorough screening and careful post-gene transfer management, replacement therapy with onasemnogene abeparvovec-xioi is safe and shows promise for early efficacy.

This paper investigates the problems arising in the construction of a program to play the game of contract bridge. These problems include both the difficulty of solving the game's perfect information variant, and techniques needed to address the fact that bridge is not, in fact, a perfect information game. Gib, the program being described, involves five separate technical advances: partition search, the practical application of Monte Carlo techniques to realistic problems, a focus on achievable sets to solve problems inherent in the Monte Carlo approach, an extension of alpha-beta pruning from total orders to arbitrary distributive lattices, and the use of squeaky wheel optimization to find approximately optimal solutions to cardplay problems.Gib is currently believed to be of approximately expert caliber, and is currently the strongest computer bridge program in the world.