Ambient Petri Nets

Both the Ambient Calculus by L. Cardelli and the Elementary Object Systems by R. Valk model the behaviour of mobile systems. The Ambient Calculus is based on the concept of ambient, which is an environment with a given name that is delimited by a boundary, where some internal processes are executed. The main property of these ambients is that they can be moved to a new location thus modeling mobility. Elementary Object Systems are two-level net systems composed of a system net and one or more object nets, which can be seen as high-level token objects of the system net modeling the execution of mobile processes. This paper intends to contribute to the relationship between both frameworks by defining a multilevel extension of Elementary Object Systems, which will be used to provide a denotational semantics of a new process algebra called APBC (Ambient Petri Box Calculus). Such process algebra is an extension of the Petri Box Calculus that includes both ambients and their mobility capabilities, which conversely can be also interpreted as an extension of the Ambient Calculus with the main operations from the PBC.     

A proposal of ubiquitous fuzzy computing for Ambient Intelligence

Ambient Intelligence is considered as the composition of three emergent technologies: Ubiquitous Computing, Ubiquitous Communication and Intelligent User Interfaces. The aim of integration of aforesaid technologies is to make wider the interaction between human beings and information technology equipment through the usage of an invisible network of ubiquitous computing devices composing dynamic computational-ecosystems capable of satisfy the users requirements. Many works focus the attention on the interaction from users to devices in order to allow an universal and immediate access to available content and services provided by the environment. This paper, vice versa, focuses on the reverse interactions, from devices to users, in order to realize a collection of autonomous control services able to minimize the human effort. In particular, by merging computational intelligence methodologies with standard Web technologies we show how ubiquitous devices will be able to find the suitable set of intelligent services in a transparent way.     

An agent-based approach towards automatic service composition in ambient intelligence

Systems for Ambient Intelligence environments involve at some stage a service composition task, as a mean of adaptability to the context changes. However, users generally find themselves involved in the composition task, by selecting or deciding what to compose and how. This paper proposes the use of Artificial Intelligent Agents for the automation of the composition task, providing transparency from the user point of view.     

WINES: Wired and Wireless Intelligent Networked Systems

The UK's Engineering and Physical Sciences Research Council launched its Wired and Wireless Intelligent Networked Systems program in 2004 to address research challenges in creating massive-scale ubiquitous and pervasive computing environments. WINES assumes an intelligent, pervasive information and communications technology environment would eventually emerge in which users experience a rich variety of heterogeneous services and systems, delivered through a wide range of devices.     

Human-centered ontology engineering: The HCOME methodology

The fast emergent and continuously evolving areas of the Semantic Web and Knowledge Management make the incorporation of ontology engineering tasks in knowledge-empowered organizations and in the World Wide Web more than necessary. In such environments, the development and evolution of ontologies must be seen as a dynamic process that has to be supported through the entire ontology life cycle, resulting to living ontologies. The aim of this paper is to present the Human-Centered Ontology Engineering Methodology (HCOME) for the development and evaluation of living ontologies in the context of communities of knowledge workers. The methodology aims to empower knowledge workers to continuously manage their formal conceptualizations in their day-to-day activities and shape their information space by being actively involved in the ontology life cycle. The paper also demonstrates the Human Centered ONtology Engineering Environment, HCONE, which can effectively support this methodology. George VOUROS (B.Sc. Ph.D.) holds a B.Sc. in Mathematics, and a Ph.D. in Artificial Intelligence all from the University of Athens, Greece. Currently he is a Professor and Head of the Department of Information and Communication Systems Engineering, University of the Aegean, Greece, Director of the AI Lab and head of the Intelligent and Cooperative Systems Group (InCoSys). He has done research in the areas of Expert Systems, Knowledge management, Collaborative Systems, Ontologies, and Agent-based Systems. His published scientific work includes more than 80 book chapters, journal and national and international conference papers in the above-mentioned themes. He has served as program chair and chair and member of organizing committees of national and international conferences on related topics. Konstantinos KOTIS (B.Sc. Ph.D.) holds a B.Sc. in Computation from the University of Manchester, UK (1995), and a Ph.D. in Information Management from University of the Aegean, Greece (May, 2005). Currently, he is a member of the Intelligent and Cooperative Systems Group (InCoSys) and director of the Information Technology Department of the Prefecture of Samos, Greece. His research and published work concerns Knowledge management, Ontology Engineering and Semantic Web. He has lectured in several IT seminars and has served as member of program committees in international workshops.     

An ontology-based approach to conflict resolution in Home and Building Automation Systems

Ambient intelligent systems such as Home and Building Automation Systems (HBAS) are becoming evermore accepted and capable of actuating automatically on behalf of users to fulfil their requests or enable activities. However, when multiple users interact with such systems, the requirements of activities often interfere resulting in conflicting actuations which HBAS ought to automatically detect and resolve. Yet, despite recent advances in HBAS, no ambient intelligent solution has been reported that is adequately grounded on knowledge analysis.The contributions of this article are twofold. First, it reviews relevant literature on Ambient Intelligence, conflict detection, conflict resolution and knowledge representation in HBAS. Second, it proposes and validates an ontological framework for conflict detection and resolution backed by knowledge-based analysis. Effectively, the proposed solution performs automatic environment actuations maximizing users comfort and energy efficiency.     

Soft Computing Based Pattern Classifiers for the Obstacle Avoidance Behavior of Intelligent Autonomous Vehicles (IAV)

To ensure more autonomy and intelligence with real-time processing capabilities for the obstacle avoidance behavior of Intelligent Autonomous Vehicles (IAV), the use of soft computing is necessary to bring this behavior near to that of humans in the recognition, learning, adaptation, generalization, reasoning and decision-making, and action. In this paper, pattern classifiers of spatial obstacle avoidance situations using Neural Networks (NN), Fuzzy Logic (FL), Genetic Algorithms (GA) and Adaptive Resonance Theory (ART) individually or in combination are suggested. These classifiers are based on supervised learning and adaptation paradigms as Gradient Back-Propagation (GBP), FL, GA and Simplified Fuzzy ArtMap (SFAM) resulting in NN/GBP and FL as Intelligent Systems (IS) and in NN/GA, NN/GA-GBP, NN-FL/GBP and NN-FL-ART/SFAM as Hybrid Intelligent Systems (HIS). Afterwards, a synthesis of the suggested pattern classifiers is presented where their results and performances are discussed as well as the Field Programmable Gate Array (FPGA) architectures, characterized by their high flexibility and compactness, for their implementation.     

Learning in an Ambient Intelligent World: Enabling Technologies and Practices

The rapid evolution of information and communication technology opens a wide spectrum of opportunities to change our surroundings into an Ambient Intelligent (AmI) world. AmI is a vision of future information society, where people are surrounded by a digital environment that is sensitive to their needs, personalized to their requirements, anticipatory of their behavior, and responsive to their presence. It emphasizes on greater user friendliness, user empowerment, and more effective service support, with an aim to bring information and communication technology to everyone, every home, every business, and every school, thus improving the quality of human life. AmI unprecedentedly enhances learning experiences by endowing the users with the opportunities of learning in context, a breakthrough from the traditional education settings. In this survey paper, we examine some major characteristics of an AmI learning environment. To deliver a feasible and effective solution to ambient learning, we overview a few latest developed enabling technologies in context awareness and interactive learning. Associated practices are meanwhile reported. We also describe our experience in designing and implementing a smart class prototype, which allows teachers to simultaneously instruct both local and remote students in a context-aware and natural way.     

Integrating scheduling and control functions in computer integrated manufacturing using artificial intelligence

Proper integration of scheduling and control in Flexible Manufacturing Systems will make available the required level of decision-making capacity to provide a flexibly-automated, efficient, and quality manufacturing process. To achieve this level of integration, the developments in computer technology and sophisticated techniques of artificial intelligence (AI) should be applied to such FMS functions as scheduling. In this paper, we present an Intelligent Scheduling System for FMS under development that makes use of the integration of two AI technologies. These two AI technologies — Neural Networks and Expert Systems — provide the intelligence that the scheduling function requires in order to generate goodschedules within the restrictions imposed by real-time problems. Because the system has the ability to plan ahead and learn, it has a higher probability of success than conventional approaches. The adaptive behavior that will be achieved contribute to the integration of scheduling and control in FMS.     

不确定性MPI／PVM程序的完全调试

讨论如何完全地调试不确定性MPI／PVM并行程序．在循环调试过程中,不确定性导致前次遇到的错误在以后的执行中很可能无法再现．基于MPI／PVM的FIFO通信模型,给出一种记录－重放技术的实现．通过可控制的重放,用户可以覆盖所有可能的程序执行路径,从而达到完全调试的目的．和其它方法相比,所提供的方法所需时空开销要小得多．此技术已在两种消息传递体系结构上得到实现：一种是曙光－2000超级服务器（由国家智能计算机研究中心开发）,它由单处理器（PowerPC）结点经MESH网互联而成;另一种是国家高性能计算中心（     

Combining the real world with simulations for a robust testing of Ambient Intelligence services

This paper proposes a general architecture for testing, validating and verifying Ambient Intelligence (AmI) environments: AmISim. The development of AmI is a very complex task because this technology must often adapt to contextual information as well as unpredictable behaviours and environmental features. The architecture presented deals with AmI applications in order to cover the different components of these kinds of systems: environment, users, context and adaptation. This architecture is the first one that is able to cover all these features, which are needed in a full AmI system. The paper shows that AmISim is able to cover a complete AmI system and to provide a framework which can test scenarios that would be impossible to test in real environments or even with previous simulation approaches. Simulated and real elements coexist in AmISim for a robust testing, validation and verification of the AmI systems, which provide an easier and less costly deployment.     

Reactive,proactive, and extensible situation-awareness in ambient assisted living

Considering that the world population is aging, health-support issues are in evidence, and many dangerous situations concerning users in their living environment may arise. This paper presents an approach to allow Ambient Assisted Living (AAL) systems to identify and predict situations that may endanger users in their living environment. Elderly people generally have difficulties to perform daily activities as using some electronic device, cooking, dressing among others. This paper offers an alternative to acquire comprehension of a former person's behavioral providing this knowledge when cognitive impairments will occur. This is a significant improvement to traditional expert systems applied to AAL as the handling of the knowledge base is adapted to the failing users’ behavior. We consider the user profile dynamics where new and different situations not initially planned in the development of the systems may occur. This approach was developed considering the principles of reactive and proactive behavior and the extensibility capacity of the system. Systems developed following the above-described principles can react to the current situations and anticipate proactively a dangerous situation eliminating it or controlling its impact. The approach is evaluated and verified by a case study where unwanted, dangerous situations were created and subsequently detected. The case study is based on a simulated smart house fulfilled with sensors and appliances. An application was build based on the developed approach, and it was capable of choosing the most appropriate actions to solve the unwanted situations. The main contributions of the present work are the identification and prediction of situations in smart houses, an approach developed with the principles of reactive and proactive behavior validated with a case study and supported by a probabilistic ontology.     

Energy-efficient deployment of Intelligent Mobile sensor networks

Many visions of the future include people immersed in an environment surrounded by sensors and intelligent devices, which use smart infrastructures to improve the quality of life and safety in emergency situations. Ubiquitous communication enables these sensors or intelligent devices to communicate with each other and the user or a decision maker by means of ad hoc wireless networking. Organization and optimization of network resources are essential to provide ubiquitous communication for a longer duration in large-scale networks and are helpful to migrate intelligence from higher and remote levels to lower and local levels. In this paper, distributed energy-efficient deployment algorithms for mobile sensors and intelligent devices that form an Ambient Intelligent network are proposed. These algorithms employ a synergistic combination of cluster structuring and a peer-to-peer deployment scheme. An energy-efficient deployment algorithm based on Voronoi diagrams is also proposed here. Performance of our algorithms is evaluated in terms of coverage, uniformity, and time and distance traveled until the algorithm converges. Our algorithms are shown to exhibit excellent performance.     

Generating help for users of application software

Help for users of Information Processing Systems (IPSs) is typically based upon the presentation of pre-stored texts written by the system designers for predictable situations. Though advances in user interface technology have eased the process of requesting advice, current on-line help facilities remain tied to a back-end of canned answers, spooled onto users, screens to describe queried facilities.This paper argues that the combination of a user's knowledge of an application and the particular states which a system can assume require different answers for the large number of possible situations. Thus, a marriage of techniques from the fields of text generation and Intelligent Help Systems research is needed to construct responses dynamically. Furthermore, it is claimed that the help texts should attempt to address not only the immediate needs of the user, but to facilitate learning of the system by incorporating a variety of educational techniques to specialise answers in given contexts.A computational scheme for help text generation based on schema of rhetorical predicates is presented. Using knowledge of applications programs and their users, it is possible to provide a variety of answers in response to a number of questions. The approach uses object-oriented techniques to combine different information from a variety of sources in a flexible manner, yielding responses which are appropriate to the state of the IPS and to the user's level of knowledge.Modifications to the scheme which resulted from its evaluation in the EUROHELP project are described, together with ongoing collaborative work and further research developments.Colin Tattersall is a Research Fellow at the Computer Based Learning Unit. He completed his B. Sc. in Computational Studies at Leeds University in 1986, then joined the CBL Unit on an ESRC studentship linked to ESPRIT project P280 EUROHELP. Within the project, his work related to knowledge representation and text generation for intelligent help systems, leading to a Ph.D. in mid-1990 entitled Question-answering and explanation in online help systems: a knowledge-based approach. The work was followed by a year-long fellowship, funded by ICL, to investigate the commercial viability of advanced help system architectures. This paper reflects results and experience gained from both research and development of intelligent help systems.     

GABRIEL: Gis Activity-Based tRavel sImuLator. Activity Scheduling in the Presence of Real-Time Information

A series of travel simulators have been developed in the past two decades under the Intelligent Transportation Systems (ITS) umbrella. They have addressed issues such as reactions to advisory radio and variable message signs, use of navigation systems, route diversion, and mode choice. The objective of this paper is to present the design and implementation of a different kind of travel simulator. GABRIEL (Gis Activity-Based tRavel sImuLator) has as a foundation the activity-based approach and makes use of geographic information systems (GIS) as a development environment. The simulation scenario consists of a commute trip where two activities take place. En-route to the first destination, congestion occurs and subjects are requested to take action based on a set of alternatives. The simulator provides re-routing, destination substitution, dynamic geographic information and real-time information to aid users in their decision-making process. As a result it helps subjects in developing their ability to adapt given a particular scenario and allow researchers in understanding trip making, activity rescheduling, and the decision-making process from a comprehensive perspective.

Heterogeneous learning in the Doppelgänger user modeling system

Doppelgänger is a generalized user modeling system that gathers data about users, performs inferences upon the data, and makes the resulting information available to applications.Doppelgänger's learning is calledheterogeneous for two reasons: first, multiple learning techniques are used to interpret the data, and second, the learning techniques must often grapple with disparate data types. These computations take place at geographically distributed sites, and make use of portable user models carried by individuals. This paper concentrates onDoppelgänger's learning techniques and their implementation in an application-independent, sensor-independent environment.     

CAD智能工程数据库集成系统

从设计过程入手,通过对共性工程数据及其关系的讨论,基于C/S结构的分布式计算,引入知识工程,建立知识库,应用推理机制,提出了一种CAD技术集成方案和系统实现原型,通过开发方便的操作工具,使得共性工程数据库中的数据的使用和管理具有智能化,方便设计人员使用和提高设计效率。     

Exchanging courses between different Intelligent Tutoring Systems: A generic course generation authoring tool

In recent years a great effort has been made in order to create Intelligent Tutoring Systems that get close to human teaching. Some of the handicaps of the systems already created are the impossibility of sharing the courses between different Intelligent Tutoring Systems and the difficulty of creating them. Once the intelligent tutoring system is created, creating a new course is an expensive job that requires the intervention of many people that are expert in different areas. In this paper a generic and extensible authoring tool to create courses for different Intelligent Tutoring Systems is presented. This authoring tool allows the creation of courses for different types of intelligent tutoring systems. Once a course is created it can be exported to another intelligent tutoring system, reusing the domain model that the course represents. The prototype of the authoring tool has been tested with two simple Intelligent Tutoring Systems.     

Bringing chatbots into education: Towards natural language negotiation of open learner models

There is an extensive body of work on Intelligent Tutoring Systems: computer environments for education, teaching and training that adapt to the needs of the individual learner. Work on personalisation and adaptivity has included research into allowing the student user to enhance the system’s adaptivity by improving the accuracy of the underlying learner model. Open Learner Modelling, where the system’s model of the user’s knowledge is revealed to the user, has been proposed to support student reflection on their learning. Increased accuracy of the learner model can be obtained by the student and system jointly negotiating the learner model. We present the initial investigations into a system to allow people to negotiate the model of their understanding of a topic in natural language. This paper discusses the development and capabilities of both conversational agents (or chatbots) and Intelligent Tutoring Systems, in particular Open Learner Modelling. We describe a Wizard-of-Oz experiment to investigate the feasibility of using a chatbot to support negotiation, and conclude that a fusion of the two fields can lead to developing negotiation techniques for chatbots and the enhancement of the Open Learner Model. This technology, if successful, could have widespread application in schools, universities and other training scenarios.