virtual knowledge communities for corporate knowledge issues pierre maret insa de lyon, liris,...

Virtual Knowledge Communities for Corporate Knowledge Issues

Pierre MaretINSA de Lyon, LIRIS, France

Mark Hammond Imperial College London, England

Jacques CalmetUniversity of Karlsruhe, IAKS, Gernamy

Virtual Knowledge Communities. Maret, Hammond, Calmet

Overview

Dynamical distributed knowledge management Enterprise considered as a distributed

computational paradigm Agent-oriented approach

Modeling dynamical knowledge exchanges within agents

Concept of “Virtual knowledge communities”


Agenda

Knowledge Management MAS for corporate knowledge Liberal approach of agents and Agent Oriented Abstraction Agent’s Knowledge Virtual knowledge communities

– Modeling– Processes– Social behavior

Implementation and example Results, Perspectives


Enterprise Knowledge Management

What is it? Models, techniques, methods

related to the improvement of activity through formalizing, exchanging, reusing knowledge

Key words– Knowledge intensive tasks– Ontology– Information, Data, Documents– Community of practice, community of interest


Enterprise Knowledge Management

Most approaches to knowledge management rely on centralization and objectivity (Database paradigm) :

One database schema and one ontology for structuring and indexing the organization’s universe. Eventually distributed databases.

Incompatible with the very nature of knowledge: subjective, distributed and contextual

Bonifacio: "all perspectival aspects of knowledge should be eliminated in favor of an objective and general representation of knowledge".

Authors emphasizes distributed knowledge management and knowledge nodes.

Knowledge Node 1KN 3KN 2

Ontology 1

O2 O3translation translation


Corporate Knowledge - Definition

Overall knowledge possessed within an organization + Abilities for exchanges

Comments:– Covers individuals, data bases, documents, sensors…– Large definition of knowledge: everything that can be useful

for acting within the organization (piece of information, predicate, protocol…)

– Linked to the agents’ decision mechanism : domains of interests, knowledge exchange processes


MAS for Knowledge Management

Overview of agents in KM: [Dignum 04] Motivations for using MAS approachCompatible with

– Distribution of data, capabilities, responsibilities.– Autonomy AND complex interactions (negotiation,

information sharing, coordination)– Dynamic behavior and responsive to changes


MAS for Knowledge Management

Two perspectives :

Agents to implement KM functionalities

Agents to model the organizational KM environment

Needs: Broad and generic view on knowledge within the organization (Content, Processes, …)


Bases of our proposal

Liberal approach of agent societies

Agent-Oriented Abstraction (AOA)


Liberal approach of agents societies

[Calmet 03] (Esaw) Model for a society of agents based on sociology

principles (Weber)Main contents No general goals imposed to agents (goals arise from

agents’ actions) The system is open and security is assumed Knowledge heterogeneity must be supported


Agent-Oriented Abstraction (AOA)

[Calmet 04] (to appear) An agent is composed of

- Annotated Knowledge

- A Decision Mechanism

A generic approach for agents and society of agents

The present work concentrates on the knowledge component


Corporate Knowledge, 2nd definition

Overall knowledge possessed by agents of an organization

Comments:– Agents: includes individuals and automata– Large definition of knowledge (includes cooperation ability)– Linked to the agents’ decision mechanism : actions related

to knowledge processes (exchanges, domains of interests)

Our goal : Model the organizational environment for CK and agent’s ability to share knowledge


Agent’s Knowledge

Knowledge Cluster : structured knowledge related to a given area (task, topic…), expressed in terms of predicate, concepts, actions (+ sub-cluster: recursive definition)

Knowledge instances = instances of terms

Agents’ knowledge = a knowledge cluster + knowledge instances


Agent’s Knowledge

Comments Knowledge varies from agent to agent : agents do

not have the same view of the world Knowledge evolves with time: inherent knowledge +

knowledge production and acquisition– Instances– Knowledge cluster

Fully compliant with very nature of corporate knowledge


Sharing Knowledge

Agent possess knowledge They are in charge of given tasks and They can increase their efficiency thanks to

knowledge exchanges

=>Modeling agent’s behavior in knowledge sharing=>Added feature which must be opened, dynamic,

agent-driven : Virtual Knowledge Communities


Virtual Knowledge Communities VKC

A VKC: first class abstraction A topic, a leader, members, a space Topic: subpart of leader’s knowledge Leader: any agent Members: any others agents Space: message buffer controlled by the leader


VKC Processes

Initiate: an agent proposes a topic (sub-cluster and/or instances)

Join: an agent is interested by a community topic (cluster intersection)

Inform: an agent proposes an extension to a topic Request: an agent asks for extensions of a topic Leave, delete…

Agents can create and join many communities


Agent’s behavior

Agents have an added layer Additional goals: in terms of knowledge cluster to

extend Examples of behavior:

– Individualistic agent: acts to reach its goals (ex: kill/leave a community once completing knowledge it required)

– Social agent: acts to help others agents (ex: join all communities related to its knowledge)


Implementation & Example

Jade Plate-form + Java agents

Agent1: Jose

J-ItemJ-Book is_a J-ItemMyBook instance_of J-BookJ-Item = Item

Agent2: Mark

M-ItemM-Item = Item





M-ItemM-Item = Item

Goal: M-ItemCreate community on “Item”

Agent1: JoseTask T1

Agent2: MarkTask T2

Additional behavior





M-ItemM-Item = Item

Goal: M-Item

Agent1: Jose Agent2: Mark

Join Mark’s community on “Item”





M-ItemM-Item = Item

Goal: M-Item

Informs about J-Book is_a ItemMyBook instance of J-Book






M-ItemM-Item = Item


IntroducesM-Book = J-Book





M-ItemM-Book is-a M-ItemM-Item = ItemM-Book = J-BookMyBook instance of M-Book



Results

Knowledge exchanged depending on agent’s goals and decisions

An organizational environment for corporate knowledge

Implementation of the liberal approach of agents in the context of corporate knowledge: openness, autonomy, dynamicity in knowledge exchange

Agent-Oriented Abstraction: emphasizes duality / complementarities in-between Knowledge and Decision


Perspectives

Application to knowledge filtering within organization, personal assistant software

Security issues: ensure only trustworthy agents Modeling agent’s knowledge: annotations as

proposed in AOA (traditional agent plate-forms are not sufficient)

Introducing more complex behaviors/roles