Approximate reasoning using terminological models

Term Subsumption Systems (TSS) form a knowledge-representation scheme in AI that can express the defining characteristics of concepts through a formal language that has a well-defined semantics and incorporates a reasoning mechanism that can deduce whether one concept subsumes another. However, TSS's have very limited ability to deal with the issue of uncertainty in knowledge bases. The objective of this research is to address issues in combining approximate reasoning with term subsumption systems. To do this, we have extended an existing AI architecture (CLASP) that is built on the top of a term subsumption system (LOOM). First, the assertional component of LOOM has been extended for asserting and representing uncertain propositions. Second, we have extended the pattern matcher of CLASP for plausible rule-based inferences. Third, an approximate reasoning model has been added to facilitate various kinds of approximate reasoning. And finally, the issue of inconsistency in truth values due to inheritance is addressed using justification of those values. This architecture enhances the reasoning capabilities of expert systems by providing support for reasoning under uncertainty using knowledge captured in TSS. Also, as definitional knowledge is explicit and separate from heuristic knowledge for plausible inferences, the maintainability of expert systems could be improved

Concurrent Lexicalized Dependency Parsing: The ParseTalk Model

A grammar model for concurrent, object-oriented natural language parsing is introduced. Complete lexical distribution of grammatical knowledge is achieved building upon the head-oriented notions of valency and dependency, while inheritance mechanisms are used to capture lexical generalizations. The underlying concurrent computation model relies upon the actor paradigm. We consider message passing protocols for establishing dependency relations and ambiguity handling.Comment: 90kB, 7pages Postscrip

Towards Interactive, Incremental Programming of ROS Nodes

Writing software for controlling robots is a complex task, usually demanding command of many programming languages and requiring significant experimentation. We believe that a bottom-up development process that complements traditional component- and MDSD-based approaches can facilitate experimentation. We propose the use of an internal DSL providing both a tool to interactively create ROS nodes and a behaviour-replacement mechanism to interactively reshape existing ROS nodes by wrapping the external interfaces (the publish/subscribe topics), dynamically controlled using the Python command line interface.Comment: Presented at DSLRob 2014 (arXiv:cs/1411.7148

Next generation software environments : principles, problems, and research directions

The past decade has seen a burgeoning of research and development in software environments. Conferences have been devoted to the topic of practical environments, journal papers produced, and commercial systems sold. Given all the activity, one might expect a great deal of consensus on issues, approaches, and techniques. This is not the case, however. Indeed, the term "environment" is still used in a variety of conflicting ways. Nevertheless substantial progress has been made and we are at least nearing consensus on many critical issues.The purpose of this paper is to characterize environments, describe several important principles that have emerged in the last decade or so, note current open problems, and describe some approaches to these problems, with particular emphasis on the activities of one large-scale research program, the Arcadia project. Consideration is also given to two related topics: empirical evaluation and technology transition. That is, how can environments and their constituents be evaluated, and how can new developments be moved effectively into the production sector

Software process modelling as relationships between tasks

Systematic formulation of software process models is currently a challenging problem in software engineering. We present an approach to define models covering the phases of specification, design, implementation and testing of software systems in the component programming framework, taking into account non-functional aspects of software (efficiency, etc.), automatic reusability of implementations in systems and also prototyping techniques involving both specifications and implementations. Our proposal relies on the identification of a catalogue of tasks that appear during these phases which satisfy some relationships concerning their order of execution. A software process model can be defined as the addition of more relationships over these tasks using a simple, modular process language. We have developed also a formal definition of correctness of a software development with respect to a software process model, based on the formulation of models as graphs.Peer ReviewedPostprint (published version

PCLIPS: Parallel CLIPS

PCLIPS (Parallel CLIPS) is a set of extensions to the C Language Integrated Production System (CLIPS) expert system language. PCLIPS is intended to provide an environment for the development of more complex, extensive expert systems. Multiple CLIPS expert systems are now capable of running simultaneously on separate processors, or separate machines, thus dramatically increasing the scope of solvable tasks within the expert systems. As a tool for parallel processing, PCLIPS allows for an expert system to add to its fact-base information generated by other expert systems, thus allowing systems to assist each other in solving a complex problem. This allows individual expert systems to be more compact and efficient, and thus run faster or on smaller machines