A theoretical framework on proactive information exchange in agent teamwork

Proactive information delivery is critical to achieving effective teamwork. However, existing theories do not adequately address proactive information delivery. This paper presents a formal framework for proactive information delivery in agent teamwork. First, the concept of information need is introduced. Second, a new modal operator, InfoNeed is used to represent information needs. The properties of the InfoNeed operator and its relationships to other mental modal operators are examined, four types of information needs are formally identified, and axioms for anticipating the information needs of other agents are proposed and justified. Third, the axiom characterizing chains of helpful behavior in large agent teams is given. Fourth, the semantics for two proactive communicative acts (ProInform and 3PTSubscribe) is given using a reformulation of the Cohen-Levesque semantics for communicative acts in terms of the SharedPlans formalism of Grosz and Kraus. The work in this paper not only provides a better understanding of the underlying assumptions required to justify proactive information delivery behavior, but also provides a coherent basis for the specification and design of agent teams with proactive information delivery capabilities.     

A general framework for architecture composability

Architectures depict design principles: paradigms that can be understood by all, allow thinking on a higher plane and avoiding low-level mistakes. They provide means for ensuring correctness by construction by enforcing global properties characterizing the coordination between components. An architecture can be considered as an operator A that, applied to a set of components \({\mathcal{B}}\), builds a composite component \({A(\mathcal{B})}\) meeting a characteristic property \({\Phi}\). Architecture composability is a basic and common problem faced by system designers. In this paper, we propose a formal and general framework for architecture composability based on an associative, commutative and idempotent architecture composition operator \({\oplus}\). The main result is that if two architectures A ₁ and A ₂ enforce respectively safety properties \({\Phi_{1}}\) and \({\Phi_{2}}\), the architecture \({A_{1} \oplus A_{2}}\) enforces the property \({\Phi_{1} \land \Phi_{2}}\), that is both properties are preserved by architecture composition. We also establish preservation of liveness properties by architecture composition. The presented results are illustrated by a running example and a case study.     

Collaborative learning using service-oriented architecture: A framework design

Collaborative learning serves as an important part of e-learning, increasing interactivity and accessibility to various learning resources either synchronously or asynchronously among users. Distributed interactivity through Web services thus forms the focus of this paper. The paper reviews related work on service-oriented architecture (SOA), distributed infrastructure, business process management (BPM) and highlights the need to integrate SOA technologies for meaningful and interactive collaborative learning processes. The significance of the study is an SOA approach to enhance the interoperability, flexibility and reusability of e-learning content in a collaborative environment.     

SDIF:一个面向服务架构的数据整合框架

目前面向服务架构系统中,基于XML方式的异构数据整合方案存在着数据表示杂乱,缺乏领域模型的融合,以至于需要花费大量的精力去处理系统与服务数据的转化和硬编码,很难形成可复用的方案.针对这些问题,提出了一个基于SDO的面向服务数据整合架构(SDIF),引入了Object Teams机制来构建可复用的数据整合框架以及与现有系统衔接的基础设施.     

From eager to lazy constrained data acquisition: A general framework

^*1 Constraint Satisfaction Problems (CSPs)¹⁷⁾ are an effective framework for modeling a variety of real life applications and many techniques have been proposed for solving them efficiently. CSPs are based on the assumption that all constrained data (values in variable domains) are available at the beginning of the computation. However, many non-toy problems derive their parameters from an external environment. Data retrieval can be a hard task, because data can come from a third-party system that has to convert information encoded with signals (derived from sensors) into symbolic information (exploitable by a CSP solver). Also, data can be provided by the user or have to be queried to a database. For this purpose, we introduce an extension of the widely used CSP model, called Interactive Constraint Satisfaction Problem (ICSP) model. The variable domain values can be acquired when needed during the resolution process by means of Interactive Constraints, which retrieve (possibly consistent) information. A general framework for constraint propagation algorithms is proposed which is parametric in the number of acquisitions performed at each step. Experimental results show the effectiveness of the proposed approach. Some applications which can benefit from the proposed solution are also discussed. This paper is an extended and revised version of the paper presented at IJCAI’99 (Stockholm, August 1999)⁴⁾. Paola Mello, Ph.D.: She received her degree in Electronic Engineering from University of Bologna, Italy, in 1982 and her Ph.D. degree in Computer Science in 1989. Since 1994 she is full Professor. She is enrolled, at present, at the Faculty of Engineering of the University of Bologna where she teaches Artificial Intelligence. Her research activity focuses around: programming languages, with particular reference to logic languages and their extensions towards modular and object-oriented programming; artificial intelligence; knowledge representation; expert systems. Her research has covered implementation, application and theoretical aspects and is presented in several national and international publications. She took part to several national (Progetti Finalizzati e MURST) and international (UE) research projects in the context of computational logic. Michela Milano, Ph.D.: She is a Researcher in the Department of Electronics, Computer Science and Systems at the University of Bologna. From the same University she obtained her master degree in 1994 and her Ph.D. in 1998. In 1999 she had a post-doc position at the University of Ferrara. Her research focuses on Artificial Intelligence, Constraint Satisfaction and Constraint Programming. In particular, she worked on using and extending the constraint-based paradigm for solving real-life problems such as scheduling, routing, object recognition and planning. She has served on the program committees of several international conferences in the area of Constraint Satisfaction and Programming, and she has served as referee in several related international journals. Marco Gavanelli: He is currently a Ph.D. Student in the Department of Engineering at the University of Ferrara, Italy. He graduated in Computer Science Engineering in 1998 at the University of Bologna, Italy. His research interest include Artificial Intelligence, Constraint Logic Programming, Constraint Satisfaction and visual recognition. He is a member of ALP (the Association for Logic Programming) and AI^*IA (the Italian Association for Artificial Intelligence). Evelina Lamma, Ph.D.: She got her degree in Electrical Engineering at the University of Bologna in 1985, and her Ph.D. in Computer Science in 1990. Her research activity centers on logic programming languages, Artificial Intelligence and software engineering. She was co-organizers of the 3rd International Workshop on Extensions of Logic Programming ELP92, held in Bologna in February 1992, and of the 6th Italian Congress on Artificial Intelligence, held in Bologna in September 1999. She is a member of the Executive Committee of the Italian Association for Artificial Intelligence (AI^*IA). Currently, she is Full Professor at the University of Ferrara, where she teaches Artificial Intelligence and Fondations of Computer Science. Massimo Piccardi, Ph.D.: He graduated in electronic engineering at the University of Bologna, Italy, in 1991, where he received a Ph.D. in computer science and computer engineering in 1995. He currently an assistant professor of computer science with the Faculty of Engineering at the University of Ferrara, Italy, where he teaches courses on computer architecture and microprocessor systems. Massimo Piccardi participated in several research projects in the area of computer vision and pattern recognition. His research interests include architectures, algorithms and benchmarks for computer vision and pattern recognition. He is author of more than forty papers on international scientific journals and conference proceedings. Dr. Piccardi is a member of the IEEE, the IEEE Computer Society, and the International Association for Pattern Recognition — Italian Chapter. Rita Cucchiara, Ph.D.: She is an associate professor of computer science at the Faculty of Engineering at the University of Modena and Reggio Emilia, Italy, where she teaches courses on computer architecture and computer vision. She graduated in electronic engineering at the University of Bologna, Italy, in 1989 and she received a Ph.D. in electronic engineering and computer science from the same university in 1993. From 1993 to 1998 she been an assistant professor of computer science with the University of Ferrara, Italy. She participated in many research projects, including a SIMD parallel system for vision in the context of an Italian advanced research program in robotics, funded by CNR (the Italian National Research Council). Her research interests include architecture and algorithms for computer vision and multimedia systems. She is author of several papers on scientific journals and conference proceedings. She is member of the IEEE, the IEEE Computer Society, and the International Association for Pattern Recognition — Italian Chapter.     

CAFES: A framework for intrachip application modeling and communication architecture design

This paper describes CAFES, an extensible, open-source framework supporting several tasks related to high-level modeling and design of applications employing complex intrachip communication infrastructures. CAFES comprises several built-in models, including application, communication architecture, energy consumption and timing models. It also includes a set of generic and specific algorithms and additional supporting tools, which jointly with the cited models allow the designer to describe and evaluate applications requirements and constraints on specified communication architectures. Several examples of the use of CAFES underline the usefulness of the framework. Some of these are approached in this paper: (i) a realistic application captured at high-level that has its computation time estimated after mapping at the clock cycle level; (ii) a multi-application system that is automatically mapped to a large intrachip network with related tasks occupying contiguous areas in the chip layout; (iii) a set of mapping algorithms explored to define trade-offs between run time and energy savings for small to large intrachip communication architectures.     

A framework for developing home automation systems: From requirements to code

This article presents an integrated framework for the development of home automation systems following the model-driven approach. By executing model transformations the environment allows developers to generate executable code for specific platforms. The tools presented in this work help developers to model home automation systems by means of a domain specific language which is later transformed into code for home automation specific platforms. These transformations have been defined by means of graph grammars and template engines extended with traceability capabilities. Our framework also allows the models to be reused for different applications since a catalogue of requirements is provided. This framework enables the development of home automation applications with techniques for improving the quality of both the process and the models obtained. In order to evaluate the benefits of the approach, we conducted a survey among developers that used the framework. The analysis of the outcome of this survey shows which conditions should be fulfilled in order to increase reusability.     

The ECORA framework: A hybrid architecture for context-oriented pervasive computing

An infrastructure approach to support context-aware pervasive computing is advantageous for rapid prototyping of context-aware distributed applications and beneficial for unifying modelling of context and reasoning in uncertain conditions. This paper presents the ECORA framework for context-aware computing, which is designed with a focus on reasoning about context under uncertainty and addressing issues of heterogeneity, scalability, communication and usability. The framework follows an agent-oriented hybrid approach, combining centralized reasoning services with context-aware, reasoning capable mobile software agents. The use of a centralized reasoning engine provides powerful reasoning capabilities and deploying context-aware mobile agents enables agility and robustness of components in the pervasive system. The design and implementation of the framework at different levels, as well as three case studies, are presented.     

A software architecture framework for on-line option pricing

The problem of growing computational complexity in the finance industry demands manageable, high-speed and real-time solutions in solving complex mathematical problems such as option pricing. In current option trading scenarios, determining a fair price for options “any time” and “anywhere” has become vital yet difficult computational problem. In this study, we have designed, implemented, and deployed an architecture for pricing options on-line using a hand-held device that is J2ME-based Mobile computing-enabled and is assisted by web mining tools. In our architecture, the client is a MIDP user interface, and the back end servlet runs on a standalone server bound to a known port address. In addition, the server uses table-mining techniques to mine real-time data from reliable web sources upon the mobile trader’s directive. The server performs all computations required for pricing options since mobile devices have limited battery power, low bandwidth, and low memory. We have parallelized and implemented various computational techniques such as binomial lattice and finite differencing. To the best of our knowledge, this is one of the first studies that facilitate the mobile-enabled-trader to compute the price of an option in ubiquitous fashion. This architecture aims at providing the trader with various computational techniques to avail (to provide results from approximate to accurate results) while on-the-go and to make important and effective trading decisions using the results that will ensure higher returns on investments in options.

From remote tool to shared roles

This article explores teleoperation for remote presence applications from a human?robot interaction (HRI) perspective to create a model that captures the key elements of the system and projects the impact of ever-increasing advances in autonomy and communications connectivity. Remote presence applications are those where one or more humans use the robot to project themselves into an environment to complete a time-critical mission. In these applications, there is some compelling need to have human perception at a distance. For example, the environment may be unsafe or unreachable, such as encountered when searching for survivors in the aftermath of a disaster, or the situation is novel and perceptually unconstrained, as in noticing a hidden terrorist during a hostage situation. Remote presence applications are characterized by the observers won't know what needs to be seen until they see it flavor and the need to see that critical what needs to be seen in as near real time as possible. This means that remote presence applications are inherently teleoperated; the human is an active element in the control loop, and there is no benefit to full autonomy. The question becomes how to transfer the advances in autonomy and communications to enable the human-robot enterprise to successfully and reliably complete its mission.     

From enterprise architecture to business models and back

In this study, we argue that important IT change processes affecting an organization’s enterprise architecture are also mirrored by a change in the organization’s business model. An analysis of the business model may establish whether the architecture change has value for the business. Therefore, in order to facilitate such analyses, we propose an approach to relate enterprise models specified in ArchiMate to business models, modeled using Osterwalder’s Business Model Canvas. Our approach is accompanied by a method that supports business model-driven migration from a baseline architecture to a target architecture and is demonstrated by means of a case study.     

A software architecture and framework for Web-based distributed Decision Support Systems

This paper presents an integrated method to help design and implement a Web-based Decision Support Systems (DSS) in a distributed environment. First, a layered software architecture is presented to assist in the design of a Web-based DSS. The layered software architecture can provide a formal and hierarchical view of the Web-based DSS at the design stage. Next, a component-based framework is presented to implement the Web-based DSS in a distributed environment. Finally, an instance of the layered software architecture and 3CoFramework applied to the Web-based National Agricultural Decision Support System (NADSS) is presented.     

From soft constraints to bipolar preferences: modelling framework and solving issues

Real-life problems present several kinds of preferences. We focus on problems with both positive and negative preferences, which we call bipolar preference problems. Although seemingly specular notions, these two kinds of preferences should be dealt with differently to obtain the desired natural behaviour. We technically address this by generalising the soft constraint formalism, which is able to model problems with one kind of preference. We show that soft constraints model only negative preferences, and we add to them a new mathematical structure which allows to handle positive preferences as well. We also address the issue of the compensation between positive and negative preferences, studying the properties of this operation. Finally, we extend the notion of arc consistency to bipolar problems, and we show how branch and bound (with or without constraint propagation) can be easily adapted to solve such problems.     

Technical framework for Internetware: An architecture centric approach

Being a new software paradigm evolved by the Internet, Internetware brings many challenges to the traditional software methods and techniques. Sponsored by the national basic research program （973）, researchers in China have developed an architecture centric technical framework for the definition, incarnation and engineering of Internetware. First of all, a software model for Internetware is defined for what to be, including that Internetware entities should be packaged as components, behaving as agents, interoperating as services, collaborating in a structured and on demand manner, etc. Secondly, a middleware for Internetware is designed and implemented for how to be, including that Internetware entities are incarnated by runtime containers, structured collaborations are enabled by runtime software architecture, Internetware can be managed in a reflective and autonomic manner, etc. Thirdly, an engineering methodology for Internetware is proposed for how to do, including the way to develop Internetware entities and their collaborations by transforming and refining a set of software architectures which cover all the phases of software lifecycle, the way to identify and organize the disordered software assets by domain modeling, etc.     

Awareness and willingness to use PHR: a roadmap towards cloud-dew architecture based PHR framework

Multimedia Tools and Applications - Personal health record systems (PHR) assists people to access, manage and share their own health information. PHR is getting increasingly popular these days....