DIALOGIC: A Core Natural-Language Processing System

The DIALOGIC system translates English sentences into representations of their literal meaning in the context of an utterance. These representations, or "logical forms," are intended to be a purely formal language that is as close as possible to the structure of natural language, while providing the semantic compositionality necessary for meaning-dependent computational processing. The design of DIALOGIC (and of its constituent modules) was influenced by the goal of using it as the core language-processing component in a variety of systems, some of which are transportable to new domains of application.Engineering and Applied Science

A probabilistic framework for analysing the compositionality of conceptual combinations

Conceptual combination performs a fundamental role in creating the broad range of compound phrases utilised in everyday language. This article provides a novel probabilistic framework for assessing whether the semantics of conceptual combinations are compositional, and so can be considered as a function of the semantics of the constituent concepts, or not. While the systematicity and productivity of language provide a strong argument in favor of assuming compositionality, this very assumption is still regularly questioned in both cognitive science and philosophy. Additionally, the principle of semantic compositionality is underspecified, which means that notions of both "strong" and "weak" compositionality appear in the literature. Rather than adjudicating between different grades of compositionality, the framework presented here contributes formal methods for determining a clear dividing line between compositional and non-compositional semantics. In addition, we suggest that the distinction between these is contextually sensitive. Compositionality is equated with a joint probability distribution modeling how the constituent concepts in the combination are interpreted. Marginal selectivity is introduced as a pivotal probabilistic constraint for the application of the Bell/CH and CHSH systems of inequalities. Non-compositionality is equated with a failure of marginal selectivity, or violation of either system of inequalities in the presence of marginal selectivity. This means that the conceptual combination cannot be modeled in a joint probability distribution, the variables of which correspond to how the constituent concepts are being interpreted. The formal analysis methods are demonstrated by applying them to an empirical illustration of twenty-four non-lexicalised conceptual combinations

Actions and Events in Concurrent Systems Design

In this work, having in mind the construction of concurrent systems from components, we discuss the difference between actions and events. For this discussion, we propose an(other) architecture description language in which actions and events are made explicit in the description of a component and a system. Our work builds from the ideas set forth by the categorical approach to the construction of software based systems from components advocated by Goguen and Burstall, in the context of institutions, and by Fiadeiro and Maibaum, in the context of temporal logic. In this context, we formalize a notion of a component as an element of an indexed category and we elicit a notion of a morphism between components as morphisms of this category. Moreover, we elaborate on how this formalization captures, in a convenient manner, the underlying structure of a component and the basic interaction mechanisms for putting components together. Further, we advance some ideas on how certain matters related to the openness and the compositionality of a component/system may be described in terms of classes of morphisms, thus potentially supporting a compositional rely/guarantee reasoning.Comment: In Proceedings LAFM 2013, arXiv:1401.056

Design for a Darwinian Brain: Part 1. Philosophy and Neuroscience

Physical symbol systems are needed for open-ended cognition. A good way to understand physical symbol systems is by comparison of thought to chemistry. Both have systematicity, productivity and compositionality. The state of the art in cognitive architectures for open-ended cognition is critically assessed. I conclude that a cognitive architecture that evolves symbol structures in the brain is a promising candidate to explain open-ended cognition. Part 2 of the paper presents such a cognitive architecture.Comment: Darwinian Neurodynamics. Submitted as a two part paper to Living Machines 2013 Natural History Museum, Londo