Content uploaded by Virginia Dignum
Author content
All content in this area was uploaded by Virginia Dignum on Sep 10, 2014
Content may be subject to copyright.
A preview of the PDF is not available
Using Agent Societies to Support Knowledge Sharing
Abstract and Figures
Agent-Mediated Knowledge Management (AMKM) is a new research d irection that aims at t he c ross-fertilization b etween the KM and the a gents research fields. The realization that KM is primarily a management science, and not a computer science implies a different role for technology in KM, that of supporting and extending human interaction and learning, and therefore a need for intelligence-enhanced, integrated and personalized solutions. That i s, AMKM requires the flexible integration o f organizational and individual requirements and objectives. We present a a gent-based model for organizations that supports individual initiative a nd collaboration while prescribing a formal model for organizational processes. This model enables the development of people-oriented KM environments that focus on the collaboration between people.
Figures - uploaded by Virginia Dignum
Author content
All figure content in this area was uploaded by Virginia Dignum
Content may be subject to copyright.
... They can either be implemented as static program instances or using agents filling the role. The following list contains the most common roles in agent-based workflow or knowledgemanagement systems [Dig04b] Gatekeeper / Domain Manager (KAoS) / Area Coordinator: Depending on the form of coordination or the desired openness, the society may require an agent or institution in charge of admittance. The Gatekeeper takes on this responsibility allowing agents to enter or leave and maintaining a list of agents currently in the system. ...
In recent years the requirements for business information systems have changed. Knowledge- and process-management demand for flexible, dynamic and distributed software environments including the ability to work across the organization's boundaries. With traditional software not up to these challenges new concepts have been developed. This paper reviews the state of the art in workflow modelling, agent technology and agent-based workflow systems. It also pays tribute to the requirements of collaboration and proactivity.
... There are two general perspectives of the roles of agents in knowledge management [8]. The first is that agents implement the functionality of the system, as, for example, in [9]. ...
... Recently a new branch of AI called Agent-Mediated Knowledge Management has emerged as a result of research in the area of Knowledge Management in the context of multi-agent systems. The field shows a shift of interest from traditional knowledge management to collaboration of various, often heterogeneous, knowledge sources (Dignum, 2003). An example of a similar approach is shown in Poggi (2002) , where a multiagent system for Corporate Memory Management (CoMMa) is introduced. ...
The paper presents learning mechanisms for MAS based on Distributed Default Logic (DDL), the formalism for multi-agent knowledge representation and reason-ing. In the distributed environment learning processes provide measures to order default rules, which gives the agent better use of its local and external knowledge. Such mechanisms allow the system to work effectively in a changing environment, where basic facts and sources of information are uncertain.
... Recently, the area of Agent-Mediated Knowledge Management has emerged, which considers Knowledge Management in a multi-agent setting. A shift of interest can be observed from traditional knowledge management to the cooperation of distributed and often heterogeneous sources of knowledge [9]. In the Semantic Web knowledge is distributed throughout the Web and it can only be seen as a network of agents, each having its own knowledge base and reasoning facilities. ...
In a multi-agent system the sought information can often be found across various knowledge bases, which means that making
early assumptions can lead to hasty conclusions. In the paper we present a formalism for distributed default reasoning to
be performed by a group of agents that share knowledge in the form of a distributed default theory. The formalism is based
on default transformations, which can be used to derive answers to queries in the form of defaults. Such new defaults can
then be treated as intermediate results in the reasoning process. It is shown that passing messages containing transformed
defaults is more informative than strict statements and enables avoiding early conclusions. Moreover, the extended reasoning
features are embedded in the description logic framework.
Keywordsmulti-agent system-default logic-description logic-distributed reasoning-Distributed Description Logic
... Nowadays, there is an increasing interest in the use of peer-to-peer and multi-agent concepts in KM, mainly motivated by the fact that KM domains involve an inherent distribution of resources, problem solving capabilities and responsibilities [4,5]. That is, the integrity of the existing organizational structures and the autonomy of participants must be maintained, which calls for an autonomous and distributed representation of KM systems [6]. The use of shared representational ontologies has been questioned in [7] and a distributed architecture based on explicitly distributed ontologies has been proposed in [8]. ...
This research addresses the formation of new concepts and their corresponding ontology in a multi-agent system where individual autonomous agents try to learn new concepts by consulting several other agents. In this research individual agents create and learn their distinct conceptualization and rather than a commitment to a common ontology they use their own ontologies. In this paper multi-agent supervised learning of concepts among individual agents with diverse conceptualization and different ontologies is introduced and demonstrated through an intuitive example in which supervisors are other agents rather than a human.
... This is the most general model available. Finally there are two general perspectives on the roles of agents in knowl-edge management [11]. The first is that agents implement the functionality of the system, as, for example, in [9]. ...
Virtual communities are becoming increasingly popular, particularly on the Internet, as a means for like-minded individuals to pursue common goals. It is a way to access and to share knowledge and information among participants of such communities without physical or hardware constraints. The concept of a community of interest can be sup- ported in a virtual community in order to bring the appropriate parties together and to share their knowledge with each other. The objective of our work is to investigate a community abstraction approach to agent-based knowledge management. We propose a general model that extends the abstraction of an agent, such that it becomes an actor within a knowledge community. In our bottom-up model, agents themselves, software or human, are the members of the virtual knowledge sharing com- munities. Agents can choose to join, leave, create and destroy communities, and can be member of many communities simultaneously. A prototype design illustrates this approach.
In this chapter, we exemplify the use of Semantic Web technologies in personal computing applications called semantic desktops. These applications combine ontologies, taxonomies, and metadata in general to enhance personal information management, software application usage, and collaboration. According to the semantic desktop community (URL: semanticdesktop.org):
The use of ontologies, metadata annotations, and semantic Web protocols on desktop computers will allow the integration of desktop applications and the Web, enabling a much more focused and integrated personal information management as well as focused information distribution and collaboration on the Web beyond sending e-mails. The vision of the Semantic Desktop for personal information management and collaboration has been around for a long time: visionaries like Vannevar Bush and Doug Engelbart have formulated and partially realized these ideas.
Virtual communities are becoming increasingly popular, par-ticularly on the internet, as a means for like-minded individuals to meet, share and gain access to the information they are most interested in quickly and efficiently, from other individuals they can learn to trust. The concept of a community of practice or a community of interest can be supported in a virtual community in order to bring the appropriate parties together, to share their knowledge with each other. We propose a general model that extends the abstraction of an agent, such that it becomes an actor within a knowledge community. In our model, agents themselves, software or human, are the members of the virtual knowledge sharing communities. Agents can choose to join, leave, create and destroy communities, and can be member of many communities simultaneously. A Jade-based prototype design illustrates our approach.
In this paper we explore the concept of a Semantic Desktop in which software applications will be responsible for the automation of otherwise tedious tasks and the update of user information. We propose an ontology driven software agent solution where two major issues stand out: architecture and process. The architecture issue addresses the current static nature of information on a web page. In order to achieve the level of pro-activity desired we have to be able to identify, classify and code important bits of semantic information in a way that can be automatically manipulated by machines. The second issue relates to the strategy/strategies used to dynamically update information. Because of the variety of actions needed to update web sites e.g., monitoring changes to personal information (phone numbers, addresses, hobbies, etc.), maintaining a knowledge of institutional information, reacting to external events, reaction to political and environmental changes, etc., we hypothesize that no single strategy for maintaining dynamic information-awareness will do but that a variety of strategies need to be put into practice. We propose the creation of a community of software agents, each responsible for achieving a different set of tasks. The Semantic Desktop is achieved through the composition of the site semantics with the functionality provided by the instantiated software agents.
The new challenges and the increasing complexity of the environment in which organizations are deepened lead on to develop new strategies based on the development of Collective Cognition. These issues require the definition of new organization focused on actors learning, interacting and communicating in small groups of employees. Our aim is to present in this article the modeling of intermediation-based agent's tool for communities of practice (CoPs). This tool aims at improve interactions, negotiations and coordination among members in the process of new knowledge creation. A large number of solutions have been proposed as part of the application of agents in knowledge management and also to communities. In other hand, this system will able to consolidate and provide accesses to integrate knowledge resulting from members' actions, to manage join/leave of member control and represent negotiations between members.
The Agent Society framework that we have developed distinguishes between the mechanisms though which the structure and global behavior of the model is described and coordinated, and the aims and behavior of the serviceproviders (agents) that populate the model. In this framework contracts are used to integrate the top-down specification of organizational structures with the autonomy of participating agents. In this paper we introduce LCR, a very expressive logic for describing interaction in multi-agent systems. We also show how LCR behaves in contrary-to-duty situations common to deontic logic frameworks. LCR makes it possible to check whether agents in an agent society follow some desired interaction patterns and whether desired social states are preserved by agent activity. LCR is used as a formal basis for the framework for agents societies that we are developing.
We present a conceptual framework for agent societies that incorporates the specification of global organizational characteristics with individual aims and capabilities. The framework consists of three interrelated models each describing different aspects of the society. The organizational model describes agent societies in terms of roles, constraints and interactions rules. The social model populates the society with actual agents that realize the objectives of the society by enacting role(s) described in the organizational model. Finally, the interaction model describes the interaction commitments between those agents. The interdependencies between models are described by means of contracts. Contract rules specify commitments between agents and society concerning role enactment, and commitments between agents concerning interaction.
In this report we describe KennisNet, a community support system developed at
Achmea where developers of non-life insurance products collaboratively
construct and share a repository of knowledge items. The aims of KennisNet
are to structure, initiate and organise the sharing of knowledge within the group.
The KennisNet framework assures the continuous availability of consistent and
up to date information and knowledge. The components of the system are faceto-
face workshops and a knowledge sharing server. The model draws on
different technologies and methods such as knowledge modelling and
representation, user-centred design, intelligent agents and visualisation
Like multi-agent systems, KM collaboration environments can be seen as distributed systems where different actors, each pursuing its own goals, need to interact in order to achieve their goals and realize organizational objectives. In this paper, we present a agent-based model for organizations that supports individual initiative and collaboration while prescribing a formal model for organizational processes. This model enables the development of people-oriented KM environments that focus on the collaboration between people. The model is applied to the development of a knowledge market.
We present a global methodology for the design of agent societies that takes the organisational perspective as starting point and specifies the development steps for the design and development of an agent-based system for a particular domain. So far, most agent-oriented design methodologies haven't considered the influence of the social organisation model on the functionality and objectives of the agent society. Our approach is to provide a generic frame that directly relates to the organisational perception of the problem. Existing methodologies can be used for the development and modelling of each step.
Two main approaches to knowledge management (KM) have been followed by early adopters of the principle: the process-centred approach, that mainly treats KM as a social communication process; and the product-centred approach, that focuses on knowledge artefacts, their creation, storage and reuse in computer-based corporate memories. This distinction is evident not only in KM implementations in companies, but also in supporting methodologies and tools. This paper presents the Know-Net solution that aims to innovatively fuse the process-centred approach with the product-centred approach by developing a knowledge asset-centric design. The Know-Net solution includes a theoretical framework, a corporate transformation and measurement method and a software tool.
This paper describes the Knowledge Reuse And Fusion/Transformation (KRAFT) architecture which supports the fusion of knowledge from multiple, distributed, heterogeneous sources. The architecture uses constraints as a common knowledge interchange format, expressed against a common ontology. Knowledge held in local sources can be transformed into a common constraint language, and fused with knowledge from other sources. The fused knowledge is then used to solve some problem or deliver some information to a user. Problem solving in KRAFT typically exploits pre-existing constraint solvers. KRAFT uses an open and flexible agent architecture in which knowledge sources, knowledge fusing entities and users are all represented by independent KRAFT agents, communicating using a messaging protocol. Facilitator agents perform matchmaking and brokerage services between the various kinds of agent. KRAFT is being applied to an example application in the domain of network data services design.