Virtual Knowledge Communities for Corporate Knowledge Issues Pierre Maret INSA de Lyon, LIRIS, France Mark Hammond Imperial College London, England Jacques Calmet University of Karlsruhe, IAKS, Gernamy
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. O2 O3 Ontology 1 translation translation Knowledge Node 1 KN 2 KN 3
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 approach Compatible 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 Agent2: Mark J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Item = Item
Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Task T1 Agent2: Mark Task T2 J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Item = Item Additional behavior Goal: M-Item Create community on “Item”
Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Agent2: Mark J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Item = Item Goal: M-Item Join Mark’s community on “Item”
Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Agent2: Mark J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Item = Item Goal: M-Item Informs about J-Book is_a Item MyBook instance of J-Book
Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Agent2: Mark J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Item = Item Introduces M-Book = J-Book
Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Agent2: Mark J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Book is-a M-Item M-Item = Item M-Book = J-Book MyBook 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
