Search results for "Reasoning"
showing 10 items of 371 documents
High-level Programming and Symbolic Reasoning on IoT Resource Constrained Devices
2015
While the vision of Internet of Things (IoT) is rather inspiring, its practical implementation remains challenging. Conventional programming approaches prove unsuitable to provide IoT resource constrained devices with the distributed processing capabilities required to implement intelligent, autonomic, and self-organizing behaviors. In our previous work, we had already proposed an alternative programming methodology for such systems that is characterized by high-level programming and symbolic expressions evaluation, and developed a lightweight middleware to support it. Our approach allows for interactive programming of deployed nodes, and it is based on the simple but effective paradigm of …
Probabilistic Anomaly Detection for Wireless Sensor Networks
2011
Wireless Sensor Networks (WSN) are increasingly gaining popularity as a tool for environmental monitoring, however ensuring the reliability of their operation is not trivial, and faulty sensors are not uncommon; moreover, the deployment environment may influence the correct functioning of a sensor node, which might thus be mistakenly classified as damaged. In this paper we propose a probabilistic algorithm to detect a faulty node considering its sensed data, and the surrounding environmental conditions. The algorithm was tested with a real dataset acquired in a work environment, characterized by the presence of actuators that also affect the actual trend of the monitored physical quantities.
A Knowledge Management System based on Ontologies
2009
Recently the companies’ interest on a correct knowledge management is grown, more than interest on the mere knowledge itself. In the last few years, several projects have been carried out, with the aim of the development of innovative systems capable of collecting and sharing information. This paper proposes a Knowledge Management System, whose main feature is an ontological knowledge representation. The ontological representation of data allows of specializing the reasoning capabilities and of providing ad hoc behaviors. The system has been tested collecting and using data coming from projects and processes typical of ICT companies, and provides a Document Management System and an Expert S…
An Ontology Design Methodology for Knowledge-Based Systems with Application to Bioinformatics
2012
Ontologies are formal knowledge representation models. Knowledge organization is a fundamental requirement in order to develop Knowledge-Based systems. In this paper we present Data-Problem-Solver (DPS) approach, a new ontological paradigm that allows the knowledge designer to model and represent a Knowledge Base (KB) for expert systems. Our approach clearly distinguishes among the knowledge about a problem to resolve (answering the what to do question), the solver method to resolve it (answering the how to do question) and the type of input data required (answering the what I need question). The main purpose of the proposed paradigm is to facilitate the generalization of the application do…
Learning high-level tasks through imitation
2006
This paper presents the cognitive architecture Con-SCIS (Conceptual Space based Cognitive Imitation System), which tightly links low-level data processing with knowledge representation in the context of imitation learning. We use the word imitate to refer to the paradigm of program-level imitation: we are interested in the final effects of actions on objects, and not on the particular kinematic or dynamic properties of the motion. The same architecture is used both to analyze and represent the task to be imitated, and to perform the imitation by generalizing in novel and different circumstances. The implemented experimental scenario is a simplified two-dimensional world populated with vario…
Sub-Symbolic Semantic Layer in Cyc for Intuitive Chat-Bots
2007
The work presented in this paper aims to combine Latent Semantic Analysis methodology, common sense and traditional knowledge representation in order to improve the dialogue capabilities of a conversational agent. In our approach the agent brain is characterized by two areas: a "rational area", composed by a structured, rule-based knowledge base, and an "associative area", obtained through a data-driven semantic space. Concepts are mapped in this space and their mutual geometric distance is related to their conceptual similarity. The geometric distance between concepts implicitly defines a sub-symbolic relationship net, which can be seen as a new "subsymbolic semantic layer" automatically a…
Sub-Symbolic Knowledge Representation for Evocative Chat-Bots
2008
A sub-symbolic knowledge representation oriented to the enhancement of chat bot interaction is proposed. The result of the technique is the introduction of a semantic sub-symbolic layer to a traditional ontology-based knowledge representation. This layer is obtained mapping the ontology concepts into a semantic space built through Latent Semantic Analysis (LSA) technique and it is embedded into a conversational agent. This choice leads to a chat-bot with “evocative” capabilities whose knowledge representation framework is composed of two areas: the rational and the evocative one. As a standard ontology we have chosen the well-founded WordNet lexical dictionary, while as chat-bot the ALICE a…
Collective Reasoning over Shared Concepts for the Linguistic Atlas of Sicily
2013
In this chapter, collective intelligence principles are applied in the context of the Linguistic Atlas of Sicily (ALS - Atlante Linguistico Siciliano), an interdisciplinary research focusing on the study of the Italian language as it is spoken in Sicily, and its correlation with the Sicilian dialect and other regional varieties spoken in Sicily. The project has been developed over the past two decades and includes a complex information system supporting linguistic research; recently it has grown to allow research scientists to cooperate in an integrated environment to produce significant scientific advances in the field of ethnologic and sociolinguistic research. An interoperable infrastruc…
Phase Coherence in Conceptual Spaces for Conversational Agents
2010
This chapter attempts to enhance the traditional chatbots with associative/intuitive capabilities. According to these considerations, it tries to create a conversational agent model that takes into consideration, aside from the traditional rule - based dialogue mechanism, also some sort of intuitive reasoning ability. The aim is in attempting to overcome the rigid pattern - matching rules, proposing a "phase coherence" paradigm into a semantic space. With this locution the chapter intend that the vectors representing the elements of the dialogue are coherent with the context. The chapter trust that this intuitive - associative capability can be obtained using the LSA methodology. The repres…
A Modular Framework for Versatile Conversational Agent Building
2011
This paper illustrates a web-based infrastructure of an architecture for conversational agents equipped with a modular knowledge base. This solution has the advantage to allow the building of specific modules that deal with particular features of a conversation (ranging from its topic to the manner of reasoning of the chatbot). This enhances the agent interaction capabilities. The approach simplifies the chatbot knowledge base design process: extending, generalizing or even restricting the chatbot knowledge base in order to suit it to manage specific dialoguing tasks as much as possible.