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A Multi-agent System

for Knowledge Management

based on the Implicit Culture

Enrico Blanzieri

Paolo Giorgini



Department of Information and

Communication Technology

University of Trento









Overview



• Implicit Culture framework

• Personal Agents for Implicit Culture Support

• A MAS for Knowledge Management

• Conclusions

Implicit Culture (CoopIS 2001)



Implicit Culture is a relation between a group of

agents G and a set of agents G’ such that the

agents of the set G’ behave according to

the culture of the agents of the group G.



A System for Implicit Culture Support has

the goal of establishing an Implicit

Culture Phenomenon, that is a pair of

group G e G’ related by Implicit Culture.









System for Implicit Culture Support



Observer









Inductive Module









Composer

System for Implicit Culture Support



Observer









Inductive Module









Composer









ε⊆ P ∪ O, P set of agents and O set of objects









System for Implicit Culture Support



Observer stores in a

database the situated

executed actions of

the agents of G.

Observer DB

Inductive Module





G







Composer









ε⊆ P ∪ O, P set of agents and O set of objects

System for Implicit Culture Support

Inductive Σ

Σ

0



Observer stores in a Module

database the situated

executed actions of

the agents of G.

Observer DB

Inductive Module using

the situated executed

actions in DB and the

domain theory Σo, induces G

a validated cultural

constraint theory Σ.



Composer









ε⊆ P ∪ O, P set of agents and O set of objects









System for Implicit Culture Support

Inductive Σ

Σ

0



Observer stores in a Module

database the situated

executed actions of

the agents of G. Composer Observer DB

Inductive Module using

the situated executed

actions in DB and the

domain theory Σo, induces

G’ G

a validated cultural a

σt+1

constraint theory Σ.

c σ”t+1

Composer proposes to

a group G’ a set of b σ’t+1

scenes σ such that

their expected situated

action satisfies Σ.



ε⊆ P ∪ O, P set of agents and O set of objects

The application

Knowledge Management

Make easier the information exchange

among a group of people

Building a Multi-Agent System

based on the

Implicit Culture Framework









Personal Agents

Each agent is implemented with JADE

(Java Agent Development Environment)

Jade Agent





Active Agent

Behaviours Module Inductive

Module Inductive

DB

scheduler Sics theory Σ

Behaviour

Composer

Composer Observer

Observer SICS



Inbox Resources

Resources Group G ’ Group G

Beliefs

Beliefs

Capabilities

Capabilities

SICS inside each single Agent



Each agent is implemented with JADE

(Java Agent Development Environment)

Jade Agent





Active Agent



Behaviours







scheduler

Sics www.fs-on-line.it

http

Behaviour













Inbox Each agent has beliefs about

Resources

a local schema for organizing

Beliefs the information available to

Capabilities the user









SICS inside each single Agent





Each agent uses locally the SICS, which

observes the actions of the user and those of the

other agents

a specific communication protocol allows the SICS to

observe the actions executed by the user and the other

agents in response of its suggestions

induces theories about the user and the other

agents

modify the scenes suggesting

the user

the other agents

the agent itself

The Multi-agent System





User FIPA - platform Directory Facilitator (DF)

provides a yellow pages directory

SICS SICS

service to the agents.

PA1 Pan



Agent Resource Broker (ARB)

provides information about the

SICS

resources available outside the

SICS PAk multiagent system.

PA2

DF

User Personal agent is created and

ARB assigned to each user who

accesses the system by means of a

web browser.



User









Example



platform 1. Request(user1, pa1, ”traintable”)





SICS

PA1

User1









SICS SICS

PA3 PA2

Example



platform 1. Request(user1, pa1, ”traintable”)





SICS 2. Request(p1, p2, ”traintable”)



PA1

User1









SICS SICS

PA3 PA2









Example



platform 1. Request(user1, pa1, ”traintable”)





SICS 2. Request(p1, p2, ”traintable”)



PA1

3. Inform(pa2, pa1, ”info@trenitalia.it”+”pa3”)



User1









SICS SICS

PA3 PA2

Example



platform 1. Request(user1, pa1, ”traintable”)





SICS 2. Request(p1, p2, ”traintable”)



PA1

3. Inform(pa2, pa1, ”info@trenitalia.it”+”pa3”)



User1

4. Request(pa1, pa3, ”traintable”)









SICS SICS

PA3 PA2









Example



platform 1. Request(user1, pa1, ”traintable”)





SICS 2. Request(p1, p2, ”traintable”)



PA1

3. Inform(pa2, pa1, ”info@trenitalia.it”+”pa3”)



User1

4. Request(pa1, pa3, ”traintable”)





5. Inform(pa3, pa1, ”www.viaggi.it”)









SICS SICS

PA3 PA2

Example



platform 1. Request(user1, pa1, ”traintable”)





SICS 2. Request(p1, p2, ”traintable”)



PA1

3. Inform(pa2, pa1, ”info@trenitalia.it”+”pa3”)



User1

4. Request(pa1, pa3, ”traintable”)





5. Inform(pa3, pa1, ”www.viaggi.it”)





6. Inform(pa1, user1,”info@trenitalia.it”+“www.viaggi.it”)





SICS SICS

PA3 PA2









Example



platform 1. Request(user1, pa1, ”traintable”)





SICS 2. Request(p1, p2, ”traintable”)



PA1

3. Inform(pa2, pa1, ”info@trenitalia.it”+”pa3”)



User1

4. Request(pa1, pa3, ”traintable”)





5. Inform(pa3, pa1, ”www.viaggi.it”)





6. Inform(pa1, user1,”info@trenitalia.it”+“www.viaggi.it”)





SICS SICS 7. Inform(user1, pa1, accept(“www.viaggi.it”))



PA3 PA2

Example



platform 1. Request(user1, pa1, ”traintable”)





SICS 2. Request(p1, p2, ”traintable”)



PA1

3. Inform(pa2, pa1, ”info@trenitalia.it”+”pa3”)



User1

4. Request(pa1, pa3, ”traintable”)





5. Inform(pa3, pa1, ”www.viaggi.it”)





6. Inform(pa1, user1,”info@trenitalia.it”+“www.viaggi.it”)





SICS SICS 7. Inform(user1, pa1, accept(“www.viaggi.it”))



PA3 PA2

8. Inform(pa1, pa3, accept(“www.viaggi.it”))









Example



platform 1. Request(user1, pa1, ”traintable”)





SICS 2. Request(p1, p2, ”traintable”)



PA1

3. Inform(pa2, pa1, ”info@trenitalia.it”+”pa3”)



User1

4. Request(pa1, pa3, ”traintable”)





5. Inform(pa3, pa1, ”www.viaggi.it”)





6. Inform(pa1, user1,”info@trenitalia.it”+“www.viaggi.it”)





SICS SICS 7. Inform(user1, pa1, accept(“www.viaggi.it”))



PA3 PA2

8. Inform(pa1, pa3, accept(“www.viaggi.it”))





9. Inform(p1, pa2, accept(“www.viaggi.it”))

The Implicit Culture Phenomenon



SICS

User1 requests information

SICS PA4

to Personal Agent PA 1



PA3

SICS



SICS

PA2 PA1 interacts with

PA6

SICS other agents

PA1

SICS

PA5

PA1 propagate the

information about

the action of the user

User1 to other agents









The Implicit Culture Phenomenon



SICS

There is an improvment

SICS PA4

of knowledge !

PA2

SICS



SICS

PA3

SICS

PA6

PA1

SICS

PA5

Implementation



We have implemented:



• user interface with PHP, Java

• MAS with JADE

• Communication among agents and users

Fipa-request

Extension of Fipa-iterated contract net protocol

• Local schema about the information avaible with XML









Conclusions



• The MAS incorporates a SICS in each Agent



• The SICS is used in order to provide information to the user

and to the other agents



• The SICS observes the local actions of the users and those of

the other agents



• The SICS aims at solving the problem to increase agent’s

performance through tacit knowledge exchange



• We are currently working on the inductive Module and we

want to use the system in a real case study

References



http://www.science.unitn.it/pgiorgio/~ic



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