A Proposal to Develop Interactive Classification Technology

Research for the first year was oriented towards: 1) the design of an interactive classification tool (ICT); and 2) the development of an appropriate theory of inference for use in ICT technology. The general objective was to develop a theory of classification that could accommodate a diverse array of objects, including events and their constituent objects. Throughout this report, the term "object" is to be interpreted in a broad sense to cover any kind of object, including living beings, non-living physical things, events, even ideas and concepts. The idea was to produce a theory that could serve as the uniting fabric of a base technology capable of being implemented in a variety of automated systems. The decision was made to employ two technologies under development by the principal investigator, namely, SMS (Symbolic Manipulation System) and SL (Symbolic Language) [see debessonet, 1991, for detailed descriptions of SMS and SL]. The plan was to enhance and modify these technologies for use in an ICT environment. As a means of giving focus and direction to the proposed research, the investigators decided to design an interactive, classificatory tool for use in building accessible knowledge bases for selected domains. Accordingly, the proposed research was divisible into tasks that included: 1) the design of technology for classifying domain objects and for building knowledge bases from the results automatically; 2) the development of a scheme of inference capable of drawing upon previously processed classificatory schemes and knowledge bases; and 3) the design of a query/ search module for accessing the knowledge bases built by the inclusive system. The interactive tool for classifying domain objects was to be designed initially for textual corpora with a view to having the technology eventually be used in robots to build sentential knowledge bases that would be supported by inference engines specially designed for the natural or man-made environments in which the robots would be called upon to operate

Natural language processing in CLIME, a multilingual legal advisory system

This paper describes CLIME, a web-based legal advisory system with a multilingual natural language interface. clime is a 'proof-of-concept' system which answers queries relating to ship-building and ship-operating regulations. Its core knowledge source is a set of such regulations encoded as a conceptual domain model and a set of formalised legal inference rules. The system supports retrieval of regulations via the conceptual model, and assessment of the legality of a situation or activity on a ship according to the legal inference rules. The focus of this paper is on the natural language aspects of the system, which help the user to construct semantically complex queries using wysiwym technology, allow the system to produce extended and cohesive responses and explanations, and support the whole interaction through a hybrid synchronous/asynchronous dialogue structure. Multilinguality (English and French) is viewed simply as interface localisation: the core representations are languageneutral, and the system can present extended or local interactions in either language at any time. The development of clime featured a high degree of client involvement, and the specification, implementation and evaluation of natural language components in this context are also discussed

Putting concepts into context

Published online: 9 June 2016At first glance, conceptual representations (e.g., our internal notion of the object Blemon^) seem static; we have the impression that there is something that the concept lemon Bmeans^ (a sour, yellow, football-shaped citrus fruit) and that this meaning does not vary. Research in semantic memory has traditionally taken this Bstatic^ perspective. Consequently, only effects demonstrated across a variety of contexts have typically been considered informative regarding the architecture of the semantic system. In this review, we take the opposite approach: We review instances of context-dependent conceptual activation at many different timescales—from long-term experience, to recent experience, to the current task goals, to the unfolding process of conceptual activation itself—and suggest that the pervasive effects of context across all of these timescales indicate that rather than being static, conceptual representations are constantly changing and are inextricably linked to their contexts

The neural basis of object perception: dissociating action and semantic processing

This thesis has evaluated the roles of dorsal and ventral processing streams in recognition and use of objects. Four main empirical studies are presented. First, to investigate how the cortical brain processes semantic and action knowledge in different object-related tasks, I examined structural data from stroke patients (Chapter 2) and functional data from healthy individuals (Chapter 3) using a voxel-wise statistical analysis method. Using data of different modalities (structural CT, fMRI) from different sources (patients’ lesions; healthy subjects’ functional activity) handled with a systematic analysis approach, I attempted to find convergent evidence to support the dissociation of semantic and action processing. Second, I also looked into the potential differentiation within the mechanisms underlying object-related action (Chapter 4) and object naming (Chapter 5) separately. Overall, comparable findings were provided from the voxel-based morphometric analysis of patients’ lesion data and the fMRI study with healthy participants: an association was observed between ventral brain structures and the retrieval of semantic knowledge/object recognition while a dorsal fronto-parietal-occipital network was found to support the processing of action knowledge/object-oriented action. Specific dissociations were also observed within the representations for object-oriented actions as well as the mechanisms underlying naming of objects

The Knowledge Level in Cognitive Architectures: Current Limitations and Possible Developments

In this paper we identify and characterize an analysis of two problematic aspects affecting the representational level of cognitive architectures (CAs), namely: the limited size and the homogeneous typology of the encoded and processed knowledge. We argue that such aspects may constitute not only a technological problem that, in our opinion, should be addressed in order to build articial agents able to exhibit intelligent behaviours in general scenarios, but also an epistemological one, since they limit the plausibility of the comparison of the CAs' knowledge representation and processing mechanisms with those executed by humans in their everyday activities. In the final part of the paper further directions of research will be explored, trying to address current limitations and future challenges