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AMKM

AMKM. Agent-Mediated Knowledge Management AAAI Spring Symposium 2003 Organized by Ludger van Elst, Virginia Dignum, Andreas Abecker Presented by Adam Pease, Teknowledge. AMKM. Belief: Agent technology can aid in knowledge management

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AMKM

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  1. AMKM Agent-Mediated Knowledge Management AAAI Spring Symposium 2003 Organized by Ludger van Elst, Virginia Dignum, Andreas Abecker Presented by Adam Pease, Teknowledge

  2. AMKM • Belief: Agent technology can aid in knowledge management • Aims: Bring together KM and MAS to discuss the benefits, possibilities and added-value of cross-fertilization • Generate new ideas, collect existing ideas • Participants: ±45, Agents and KM, university and industry

  3. AMKM Sessions • Collaboration and Peer-to-Peer Support • Agent-based Community Support • Agent Models for Knowledge and Organizations • Context and Personalization • Ontologies and Semantic Web • Agents and Knowledge Engineering

  4. AMKM Discussion Sessions • Semantic Web • Tools & Methods • Research Directions • Machine Learning & Knowledge Acquisition

  5. Agents KM • Natural metaphor • Support distributed nature of knowledge • Elegant means to manage complexity • Extensibility and openness • Transparency of legacy systems

  6. KM  Agents • Organizational view • Structure • Common goals and norms • Context-awareness • Personalization • Usability • User interface

  7. Dimensions of AMKM • Content for understanding by • Machines <-> Humans • Parallels representation issues of • Very formal <-> very informal/linguistic • Long term <-> near term ? • Focusing research on • Multi-agent issues <-> interaction with any user

  8. Papers • Studies vs existence proofs vs ideas • Jackson – a study that disproved the initial hypothesis • Lawless – conflict about ill-defined problems leads to better decisions

  9. Discussion • Common knowledge (ontology) <-> diversity • A question of degree and configuration • Hierarchy of agreement?

  10. Thoughts on AMKM • Agents need to have a rich communication language • Otherwise interactions are simple and scripted • Therefore agents need to share some significant (computable) knowledge • Knowledge needs to be more useful and understandable to machines • Make the knowledge representation more computable or computers better at natural language understanding

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