In this paper, we propose a technique of predicting the execution time of PLC application programs written in Relay Ladder logic. The proposed technique divides an RLL program into several RLL blocks and then transfor...
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In this paper, we propose a technique of predicting the execution time of PLC application programs written in Relay Ladder logic. The proposed technique divides an RLL program into several RLL blocks and then transforms them into boolean logic equations. The internal states of an RLL program is analyzed and their dependencies are used as constraints when we solve the boolean logic equations. The plant information represented by exclusiveness of input contacts is also used as constraints. The constraint analysis reduces the complexity of logicprogramming as well as the worst-case timing prediction. The algorithm for partitioning variables in the logic equations is developed to reduce the complexity further.
Legally binding regulations are expressed in natural language. Yet, we cannot formally or automatically reason with regulations in that form. Defeasible logic has been used to formally represent the semantic interpret...
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In this paper we discuss different techniques for implementing an extension of logicprogramming for knowledge structuring. The extension we consider, in particular, is based on Contextual logicprogramming. Three dif...
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We present a correct goal-directed procedure for consistent logic program with integrity constraints in stable model semantics [5]. Although there are correct bottom-up procedures for every general logic program [13, ...
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The coincidence between the model-theoretic and the procedural semantics of SLD-resolution does not carry over to a Prolog system that also implements non-logical features like cut and whose depth-first search strateg...
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ID-logic uses ideas from the field of logicprogramming to extend second order logic with non-monotone inductive defintions. In this work, we reformulate the semantics of this logic in terms of approximation theory, a...
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ID-logic uses ideas from the field of logicprogramming to extend second order logic with non-monotone inductive defintions. In this work, we reformulate the semantics of this logic in terms of approximation theory, an algebraic theory which generalizes the semantics of several non-monotonic reasoning formalisms. This allows us to apply certain abstract modularity theorems, developed within the framework of approximation theory, to ID-logic. As such, we are able to offer elegant and simple proofs of generalizations of known theorems, as well as some new results.
Multi-agent systems (MAS) can take many forms depending on the characteristics of the agents populating them. Amongst the more demanding properties with respect to the design and implementation of multi-agent system i...
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ISBN:
(纸本)3540331069
Multi-agent systems (MAS) can take many forms depending on the characteristics of the agents populating them. Amongst the more demanding properties with respect to the design and implementation of multi-agent system is how these agents may individually reason and communicate about their knowledge and beliefs, with a view to cooperation and collaboration. In this paper, we present a deductive reasoning multi-agent platform using an extension of answer set programming (ASP). We show that it is capable of dealing with the specification and implementation of the system's architecture, communication and the individual agent's reasoning capacities. Agents are represented as Ordered Choice logic Programs (OCLP) as a way of modelling their knowledge and reasoning capacities, with communication between the agents regulated by uni-directional channels transporting information based on their answer sets. In the implementation of our system we combine the extensibility of the JADE framework with the flexibility of the OCT front-end to the Smodels answer set solver. The power of this approach is demonstrated by a multi-agent system reasoning about equilibria of extensive games with perfect information.
This paper aims to develop a strategy for architectural knowledge modeling in order to actively support the built heritage conservation process by fostering collaboration among stakeholders and interoperability betwee...
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This paper aims to develop a strategy for architectural knowledge modeling in order to actively support the built heritage conservation process by fostering collaboration among stakeholders and interoperability between datasets. The integration of two modeling systems, one ontology-based and one in BIM environment, seems to be the right way to meet this objective: the former is rather exhaustive to represent the semantic contents of conservation activities, especially non-geometrical data, the latter is absolutely suitable to represent the logic of the construction, above all geometrical-constructive aspects typical of any architectural organism. Thus, this study proposes a side-by-side approach to synchronize these different ways of representing reality by managing the complexity of cultural heritage on the one hand and of technology tools, such as information systems, on the other. The proposed methodology was tested on the city walls of San Ginesio (Macerata, Italy) and included different steps considering the in-use technologies (notably geomatics and information technologies) as key enablers to acquire, hierarchically order, model and enrich the knowledge of that heritage site. The result is a knowledge-led strategy moving from survey to HBIM implementation, as a way to enhance representation and management in architectural heritage processes.
SNOMED CT medical vocabulary can be used to identify complementary features in a database. This functionality is used to develop a natural language processor (NLP) for PAIRS (Physician Assistant Artificial Intelligenc...
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SNOMED CT medical vocabulary can be used to identify complementary features in a database. This functionality is used to develop a natural language processor (NLP) for PAIRS (Physician Assistant Artificial Intelligence Reference System). Although about 99% of concepts in PAIRS are present in SNOMED CT some features missing in it makes it unacceptable for any diagnostic decision support system (DDSS). Here we show that implementation of another NLP along with SNOMED CT makes it practically useful.
Constraint logicprogramming (CLP) is a powerful programming paradigm combining the advantages of logicprogramming and the efficiency of constraint solving. However, CLP presents some limitations in dealing with temp...
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