Dynamic Generation of User Communities with ...

Dynamic Generation of User Communities with Participative Knowledge Production and Contentdriven Delivery Practical Aspects of Knowledge Management (PAKM) 2002

Sinuhé Arroyo Intelligent Software Components (iSOCO), S.A. Juan Manuel Dodero Departamento de Informática Universidad Carlos III de Madrid

1

Dynamic Generation of User Communities with

1. Introduction 2. Agent-mediated approach

Participative Knowledge

?

Structure of groups

Production and Content-

?

Interaction within groups

driven Delivery

?

An example

3. Dynamics of production groups ?

Distance-based group affiliation

?

Dynamic user communities

5. Evaluation: instructional design scenario

Arroyo & Dodero — PAKM 2002

?

Design of tests

?

Experimental results

4. Conclusions and future work –2–

Introduction ? Distributed knowledge management ? KM processes ? Distributed system

acquisition

production

? Collaborative, group level issues ? Coordination needed

? Production issues ? Different interaction policies:

compete, cooperate, negotiate ? Structured interaction ? Hierarchical, participative relationship

delivery participative

authoritarian

? Delivery issues ? Content-driven ? Communities of interest ? Dynamic spawning and evolution

Arroyo & Dodero — PAKM 2002

–3–

Agent-mediated approach ? Producers’ collaboration (e.g. instructional designers) ? Asynchrony • Non-frequent synchronous meetings • Management (development, exchange, evaluation) of products (e.g.

docs, exercises, software) is asynchronous

? Logically structured action • Domain-level knowledge (e.g. subject taught) • Decision privileges (e.g. lecturers vs. assistants) • Conflicts should be reduced

? Why multi-agent? ? To facilitate coordination of creation tasks (e.g., compose a new

educational resource) ? To help performing several interaction styles (e.g., compete, cooperate, negotiate, …) ? To structure interaction in separate, but interconnected groups

Arroyo & Dodero — PAKM 2002

–4–

System features ? From a static perspective… ? Function: consolidation of knowledge that is produced ? Static structure: multi-tiered • Agents operate in tightly-coupled interaction groups • Hierarchical structure of groups • Progressive consolidation of knowledge

? From an environment-relational perspective… ? Agent-mediated interaction ? Multi-agent architecture and coordination protocol

? From a dynamic perspective… ? User agents’ membership into groups ? Groups evolution: fusion and/or division

Arroyo & Dodero — PAKM 2002

–5–

Hierarchical structure: marts Interaction group M Agent Proxy

Agent

Interaction group S1 Agent

Agent Agent

Arroyo & Dodero — PAKM 2002

Interaction group S2

Agent

Agent

Proxy Agent

Agent

–6–

Interaction within marts ? Minimal requirements ? Agent rationality can be modelled as preference relationships

k2 or relevance functions u(k)

k1 >

• Non-despite of other, more powerful schemes (v.g., fuzzy logic)

? Relevant aspects can be modelled as pairs: • Possible attributes: submitter’s hierarchical level, fulfilment of goals,

time-stamps, etc. • Non-despite of other, more powerful representations (v.g., ontologies)

? Agent interaction by exchanging messages ? proposal ( object, interaction ) message (FIPA’s propose) ? consolidate ( object, interaction ) message (FIPA’s inform) ? Multicast & reliable transport facility

Arroyo & Dodero — PAKM 2002

–7–

Consolidation protocol ? Start of protocol Ai sends proposal(ki,n) to every agent ? Ai starts distribution phase and sets timeout t0 ?

? If Ai does not receive messages referred to n during t0... Ai sends a consolidate(ki,n) to every agent ? Ai starts the consolidation phase ?

? If Ai receives a proposal(kj,n) from A j / kiki, before t1 expires, then the protocol finishes unsuccessfully.

?

? When Ai’s timeout t1 expires, the protocol finishes successfully

Arroyo & Dodero — PAKM 2002

–8–

Consolidation protocol receive any worse-evaluated start (send proposal)

Distribution Distribution

receive consolidation better-evaluated

any message

Idle

receive any worse-evaluated

t0 expires

receive proposal better-evaluated

Consolidation Consolidation t1 expires

Arroyo & Dodero — PAKM 2002

Failure receive consolidation better-evaluated

Success

–9–

Instructional design example

proposed modification: divide up chapter 5

Arroyo & Dodero — PAKM 2002

–10–

Example: course of the interaction Proposal p

Start timeout t0 A1

Proposal q

Proposal p

Start timeout t0

Proposal q

A2

A1

Proposal q

A2

u(p) < u(q) Start timeout t1

A3

u(p) < u(q) Reply with q

A3

OK Initial exchange of proposals

t0 expires

After receiving proposals

Termination: unsuccessful A1

Consolidate q A3

A2

Start timeout t1

Consolidate q

OK Consolidation after t0 expiration Arroyo & Dodero — PAKM 2002

Finish: successful A1

A2

t1 expires A3 After t1 expiration –11–

Dynamics of production groups ? Requirements ? Agents affiliate to marts depending on the kind of knowledge that

they produce ? Marts evolve (merge or divide) depending on the kind of knowledge consolidated within.

? Distance-based clustering ? Cognitive distance dk between agents and marts • dk(agent1, agent2) • dk(agent, mart) • dk(mart1, mart2)

? Built from dissimilarity between proposals’ attributes issued by

agents

? Agents are arranged to operate in the nearest mart ? Mart fusion/division ? K-clustering algorithm (v.g., COBWEB, K-SODATA) Arroyo & Dodero — PAKM 2002

–12–

Dynamic user communities ? Information brokering services ? Content-driven delivery ? Filters to deliver contents of interest ? Publish/subscribe pattern

? Communities of users ? User agents subscribe to items of interest ? User agents produce (publish) items ? Brokers’ routing tables are built ? Routing tables contain (hide) users’ layout

into communities of interest

? How to build dynamically… ? Monitor cognitive distances ? Apply k-clustering algorithm ? Re-organize membership of agents

Arroyo & Dodero — PAKM 2002

–13–

Evaluation scenario ? Learning Objects ? Curriculum units that can be

assembled to build higher-level learning contents. ? IMS/SCORM specifications ? XML manifest file ? Coordination needed

? Issues in collaboration ? Conditioned by partners’

competency ? Speed vs. quality tradeoff ? Avoid duplication of effort

Arroyo & Dodero — PAKM 2002

–14–

Design of tests ? Task ? Development of a Learning Object (TOC of a course on XML)

? Roles ? Docent coordinators + instructional designers + students

? Test scenarios ? one-mart (docent coordinators + instructional designers) ? two-mart (instructional designers + students)

? Proposals’ evaluation criteria ? Fulfilment of educational objectives + Rank + Time-stamp

? Measures ? Quality of the L.O. ? Stability of consolidated objects ? Conflicts decrease

Arroyo & Dodero — PAKM 2002

–15–

Quality (grade of fulfilment) Issued in two-mart scenario

Issued in one-mart scenario

80 75

75

75

Grade of fulfillment (%)

70 60

55

54

54

55

50 43

43

40

43

30 20 10 0 0

2

4

6

8

10

12

14

16

18

20

Proposals ordered by submission time Arroyo & Dodero — PAKM 2002

–16–

Consolidation lifetime

190288

Consolidation lifetime (time units)

200000

183027

180000 160000 140000 120000 100000 80000 60000 40000 20000

13439

7291

0

1622

2183

1

2

7401

3976 3

4

Consolidated proposals ordered by instant of consolidation

Arroyo & Dodero — PAKM 2002

–17–

Number of conflicts No. of conflicts (two-mart)

No. of conflicts (one-mart)

No. of conflicts/time unit

70,00 60,00 50,00 40,00 30,00 20,00 10,00 0,00 I1

A1

A3

Agents Arroyo & Dodero — PAKM 2002

–18–

Conclusions and future work ? Features ? Bottom-up, multi-agent approach to collaborative knowledge

production systems ? Dynamic building of user communities ? Applicable to several CSCW tasks • e-Book composition • Calendar organization

• Software development (analysis & design)

? Improvements needed ? Further validation in participative scenarios ? Mixed interaction styles to be tested ? Quantitative evaluation for dynamic evolution of marts

Arroyo & Dodero — PAKM 2002

–19–