1,177 research outputs found
Ontology reuse for multiagent systems development through pattern classification
Ontologies play a crucial role in multiagent systems (MASs) development, especially for domain knowledge modeling, interaction specifications, and behavioral aspect representation. Domainâspecific ontologies can be developed in an ad hoc or systematic manner through the incorporation of ontology development steps on the basis of agentâoriented methodologies. Developing such ontologies, however, is challenging because of the extensive amounts of knowledge and experience required. Moreover, since many ontologies cater for very specific domains, the question arises of whether some can be reused for faster systems development. This paper attempts to answer this question by proposing an ontology pattern classification scheme to allow the reuse of existing ontology knowledge for MAS development. Specifically, ontology patterns relevant to the design problem at hand are identified through the pattern classification scheme. These patterns are then reused and shared among agent software communities during the system development phase. The effectiveness of the proposed approach is validated using a restaurantâfinder MAS case study. Our findings suggest that utilization of the classified ontology patterns reduces development time and complexity when dealing with domainâspecific applications. The scheme also seems useful for software practitioners, where searching and reusing the patterns can easily be done during the analysis, design, and implementation of MAS development
An Intelligent Knowledge Management System from a Semantic Perspective
Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence
Patterns for Agent-Based Information Systems: A Case Study in Transport
International audienceIntelligent Transport Information Systems may find benefit of using agent-based solutions. Actually, transport information systems require adaptability to varying changes in offers, and unexpected occurring events. Agents and multiagent systems provide such requirements. Unfortunately, agent-based information systems such as other distributed, asynchronous, loose coupling applications are difficult to design and implement due to lack of best practices to ease development. This paper describes an approach based on software pattern reuse that facilitates engineering of these systems. Some patterns have been specified for the analysis and design of such information systems and are described here. Implementation patterns for a specific platform are sketched in perspectives of this research
Intelligent business processes composition based on mas, semantic and cloud integration (IPCASCI)
[EN]Component reuse is one of the techniques that most clearly contributes to the
evolution of the software industry by providing efficient mechanisms to create quality
software. Reuse increases both software reliability, due to the fact that it uses
previously tested software components, and development productivity, and leads to a
clear reduction in cost.
Web services have become are an standard for application development on cloud
computing environments and are essential in business process development. These
services facilitate a software construction that is relatively fast and efficient, two
aspects which can be improved by defining suitable models of reuse. This research
work is intended to define a model which contains the construction requirements of
new services from service composition. To this end, the composition is based on
tested Web services and artificial intelligent tools at our disposal.
It is believed that a multi-agent architecture based on virtual organizations is a
suitable tool to facilitate the construction of cloud computing environments for
business processes from other existing environments, and with help from ontological
models as well as tools providing the standard BPEL (Business Process Execution
Language). In the context of this proposal, we must generate a new business process
from the available services in the platform, starting with the requirement
specifications that the process should meet. These specifications will be composed of a
semi-free description of requirements to describe the new service.
The virtual organizations based on a multi-agent system will manage the tasks
requiring intelligent behaviour. This system will analyse the input (textual description
of the proposal) in order to deconstruct it into computable functionalities, which will
be subsequently treated. Web services (or business processes) stored to be reused
have been created from the perspective of SOA architectures and associated with an
ontological component, which allows the multi-agent system (based on virtual
organizations) to identify the services to complete the reuse process.
The proposed model develops a service composition by applying a standard BPEL
once the services that will compose the solution business process have been
identified. This standard allows us to compose Web services in an easy way and
provides the advantage of a direct mapping from Business Process Management
Notation diagrams
A Role-Based Approach for Orchestrating Emergent Configurations in the Internet of Things
The Internet of Things (IoT) is envisioned as a global network of connected
things enabling ubiquitous machine-to-machine (M2M) communication. With
estimations of billions of sensors and devices to be connected in the coming
years, the IoT has been advocated as having a great potential to impact the way
we live, but also how we work. However, the connectivity aspect in itself only
accounts for the underlying M2M infrastructure. In order to properly support
engineering IoT systems and applications, it is key to orchestrate
heterogeneous 'things' in a seamless, adaptive and dynamic manner, such that
the system can exhibit a goal-directed behaviour and take appropriate actions.
Yet, this form of interaction between things needs to take a user-centric
approach and by no means elude the users' requirements. To this end,
contextualisation is an important feature of the system, allowing it to infer
user activities and prompt the user with relevant information and interactions
even in the absence of intentional commands. In this work we propose a
role-based model for emergent configurations of connected systems as a means to
model, manage, and reason about IoT systems including the user's interaction
with them. We put a special focus on integrating the user perspective in order
to guide the emergent configurations such that systems goals are aligned with
the users' intentions. We discuss related scientific and technical challenges
and provide several uses cases outlining the concept of emergent
configurations.Comment: In Proceedings of the Second International Workshop on the Internet
of Agents @AAMAS201
An Ontology for Formalising Agreement Patterns in Auction Markets
Knowledge and best practices on auction systems are cur- rently disseminated across the research literature, which limits its access, reuse, evaluation and feedback by practitioners. This article presents a systematic approach to collect this knowledge as design patterns, in order to provide assistance to software developers. An ontology has been de- _ned for formalising design patterns in auction systems, with the aim of improving its searchability by software developers. Finally, a case study illustrates how the proposed pattern ontology provides assistance in the development of a dynamic pricing model for an e-commerce servic
An information assistant system for the prevention of tunnel vision in crisis management
In the crisis management environment, tunnel vision is a set of bias in decision makersâ cognitive process which often leads to incorrect understanding of the real crisis situation, biased perception of information, and improper decisions. The tunnel vision phenomenon is a consequence of both the challenges in the task and the natural limitation in a human beingâs cognitive process. An information assistant system is proposed with the purpose of preventing tunnel vision. The system serves as a platform for monitoring the on-going crisis event. All information goes through the system before arrives at the user. The system enhances the data quality, reduces the data quantity and presents the crisis information in a manner that prevents or repairs the userâs cognitive overload. While working with such a system, the users (crisis managers) are expected to be more likely to stay aware of the actual situation, stay open minded to possibilities, and make proper decisions
CoachAI: A Conversational Agent Assisted Health Coaching Platform
Poor lifestyle represents a health risk factor and is the leading cause of
morbidity and chronic conditions. The impact of poor lifestyle can be
significantly altered by individual behavior change. Although the current shift
in healthcare towards a long lasting modifiable behavior, however, with
increasing caregiver workload and individuals' continuous needs of care, there
is a need to ease caregiver's work while ensuring continuous interaction with
users. This paper describes the design and validation of CoachAI, a
conversational agent assisted health coaching system to support health
intervention delivery to individuals and groups. CoachAI instantiates a text
based healthcare chatbot system that bridges the remote human coach and the
users. This research provides three main contributions to the preventive
healthcare and healthy lifestyle promotion: (1) it presents the conversational
agent to aid the caregiver; (2) it aims to decrease caregiver's workload and
enhance care given to users, by handling (automating) repetitive caregiver
tasks; and (3) it presents a domain independent mobile health conversational
agent for health intervention delivery. We will discuss our approach and
analyze the results of a one month validation study on physical activity,
healthy diet and stress management
An Intelligent Knowledge Management System from a Semantic Perspective
Knowledge Management Systems (KMS) are important tools by whichorganizations can better use information and, more importantly, manageknowledge. Unlike other strategies, knowledge management (KM) is difficult todefine because it encompasses a range of concepts, management tasks,technologies, and organizational practices, all of which come under the umbrella ofthe information management. Semantic approaches allow easier and more efficienttraining, maintenance, and support knowledge. Current ICT markets are dominatedby relational databases and document-centric information technologies, proceduralalgorithmic programming paradigms, and stack architecture. A key driver of globaleconomic expansion in the coming decade is the build-out of broadbandtelecommunications and the deployment of intelligent services bundling. This paperintroduces the main characteristics of an Intelligent Knowledge ManagementSystem as a multiagent system used in a Learning Control Problem (IKMSLCP),from a semantic perspective. We describe an intelligent KM framework, allowingthe observer (a human agent) to learn from experience. This framework makes thesystem dynamic (flexible and adaptable) so it evolves, guaranteeing high levels ofstability when performing his domain problem P. To capture by the agent who learnthe control knowledge for solving a task-allocation problem, the control expertsystem uses at any time, an internal fuzzy knowledge model of the (business)process based on the last knowledge model
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