ing the differential semantics of rule-based models: exact and automated model reduction (revised version) Vincent Danos, Jérôme Feret, Walter Fontana, Russell Harmer, and Jean Krivine University of Edinburgh LIENS, INRIA-ENS-CNRS Harvard Medical School CNRS, Université Paris-Diderot

In domains involving procedural skills such as mathematics or programming, students often are prone to misconceptions which result in erroneous solutions. We present the ASG algorithm for generation of analogous problems of written subtraction as an extension of an intelligent tutor system (ITS) proposed by Zinn (2014). The student module of this ITS does not rely on an error library but uses a...

Semagraph II is a working group (WG 6345) supported by the CEC basic research directorate. The main aim of Semagraph II has been to mature and promulgate the research results and prototypes developed during the Semagraph I Basic Research Action (BRA 3074). This note outlines the aims and achievements of Semagraph, and provides references to key results.

In real-world classification tasks, it is difficult to collect training samples from all possible categories of the environment. Therefore, when an instance of an unseen class appears in the prediction stage, a robust classifier should be able to tell that it is from an unseen class, instead of classifying it to be any known category. In this paper, adopting the idea of adversarial learning, we...

We propose a two-layered model for computing semantic and conceptual interpretations from dependency structures. Abstract interpretation schemata generate semantic interpretations of `minimal' dependency subgraphs, while production rules whose speci cation is rooted in ontological categories derive a canonical conceptual interpretation from semantic interpretation structures. Con gurational des...

The gears are changed automatically with the automated shift transmission. In contrast to the automatic step transmission, the ASG must interrupt the tractive force when shifting. This is more clearly detectable the higher the tractive force that is interrupted. For this reason, it can be surmised that ASG will be accepted mainly in small cars. The increasing use of electronic throttle simplifi...

Analogy-based Story Generation (ASG) is a relatively under-explored approach for story generation and computational narrative. In this paper, we present the SAM (Story Analogies through Mapping) algorithm as our attempt to expand the scope and complexity of stories generated by ASG. Comparing with existing work and our prior work, there are two main contributions of SAM: it employs 1) analogica...

Abstract BAbSANT (Bilingual Semantic Associative Network Training) is a novel, theoretically motivated approach to anomia therapy for bilingual persons with aphasia (BPWA). We report on Russian-dominant, Russian–English BPWA, who was trained abstract English and Russian words. hypothesized both within- cross-language generalization when the non-dominant language trained, only within-language do...