Overview of NIAD&R

almondpitterpatterAI and Robotics

Feb 23, 2014 (3 years and 7 months ago)

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LIACC
-

March 2004

1

Distributed Artificial Intelligence
& Robotics Group

NIAD&R


NIAD&R is a member of
LIACC


Artificial Intelligence and Computer Science Laboratory



University of Porto






Overview of NIAD&R










Coordinator: Eugénio Oliveira





http://www.fe.up.pt/~eol/MEMBERS/eco_html

LIACC
-

March 2004

2

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



LIACC overview



NIAD&R main
Goals



NIAD&R through
Numbers



OUTLINE


Main
research lines



1

Models for Agents’ interaction



2

Advanced features for Autonomous Agents



3

Coordination of Agent
-
based teamwork



4

Agent
-
based Applications


Projects



Conclusions



Future work

LIACC
-

March 2004

3

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

University of Porto

NCC

F. Sciences

NIAAD

F. Economics

NIAD&R

F. Engineering

Scientific

Board

Advisory


Committee

Coordination

Board


general coordinator

~
50%

~
23%

~
27%

LIACC
-

March 2004

4

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Existe desde 1988.


No fim de 2003 incluía:


34 pessoas com
doutoramento
,


40 outros membros (estudantes de

doutoramento, bolseiros, etc.)

LIACC
-

March 2004

5

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Nos últimos 5 anos (
‘99


‘03
) foram publicados:




30

artigos publicados em
Revistas Internacionais

submetidos a
avaliação independente (13 em 2003);




105 artigos em livros

publicados pelas editoras

reconhecidas (ex. Springer), submetidos a avaliação
independente,


e com entrada no “Science citation index”




1

livro (
editado
);



16

capitulos

de livros;



133

outros artigos in
actas

de Congressos / Workshops



9

actas de congressos ou Workshops
editadas
;

LIACC
-

March 2004

6

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

(
’99
-

‘03
) foram orientadas e concluídas:



18
Teses de Doutoramento,



34

Teses de Mestrado.




Em
2004

estão a ser orientadas:



21

Teses de Doutoramento,



37
Teses de Mestrado.

LIACC
-

March 2004

7

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Nos últimos 5 anos (’99
-

‘03) foram organizados:


19

congressos / workshops


Em
2003

os membros do LIACC participaram em:


22

comissões de programa


6

editorial boards de revistas


LIACC
-

March 2004

8

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

NCC
:
-

Declarative

programming



Logic Programming Systems



Parallel Execution of Logic Programs



Constraint Programming



-

Parallel

and Distributed Systems



Concurrency, Distribution and Mobility



OO Languages for Distributed Environments



Parallel Programming Environments


-

Logic
, Language and
Computation



Formal Systems; Logic and Grammars



Complexity


-

Automatic
Evaluation

of Students Exercises



-

Geo
-
Referenced Data Processing

LIACC
-

March 2004

9

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

NIAAD
:
Data Mining

and Decision Support

Collaborative methodologies for DM & DS.

Recommendation tools for the selection of DA methods

Modeling Dynamic Systems



Modelling complex
dynamic

systems,


Advanced

Techniques in Data Mining and DA

Modelling higher order concepts using
ILP

Statistical methods for classification.

App. to the recognition of
multi
-
spectral images and bioinformatics.




Data Mining for Text and Web

LIACC
-

March 2004

10

Distributed Artificial Intelligence
& Robotics Group

NIAD&R


To develop:




Models for
inter
-
operability

in
Agent
-
based

Systems




Agent
-
based Software for practical
Applications

in DDD




To help young researchers in preparing their thesis



NIAD&R

Main Objectives:

LIACC
-

March 2004

11

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



AGENT
S

:



Computational entities including the following features:



Main Concept:



Distributed



Reactive and Communicative



Pro
-
Active



Autonomous



Other capabilities:



Mentalistic capabilities:



Beliefs, Desires, Intentions, Emotions




Multi
-
Agent Systems

LIACC
-

March 2004

12

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

What is the rationale behind our research?



Agents
Interaction

Negotiation
protocols

Coordination

of teams of Agents

Conflict

resolution

Agent
Capabilities

Learning

and Adaptation

Emotion
-
based agent architecture

Agent
Applications

Electronic Institutions for
VO

Multiple
-
Experts
DSS

Simulation

LIACC
-

March 2004

13

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



1999

2000

2001

2002


2003


Senior Res.

1

1

1

1


1

PhDs


1

2

2+1
-
1

4


4


Res.Ass.

5

6

8
-
1

13


13

Ext.Coll.

2

2

2

3


3

TOTAL

9

12

11

20


21

Tech.


_

_

_

_


_

Adm.


½


½


½ (shared) ½ (shared)

½ (shared)

Nr. of Researchers

LIACC
-

March 2004

14

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

PhD Thesis approved

1

2

1(+1)

1


1

MSc.Thesis approved

4

1

2

1


2

Theses in prep(PhD+M)



4+4

3+8


5+6

Total (Theses appr.)

5

3

4

2


3











*

Interview to TRN
-

Technical Research News Magazine

Scientific production

1999

2000

2001

2002


2003


Chap. in Books


1

1

4



1

Journ + Series


1+3

+4

1+3

2
*
+5


1+9

Proceed +TRep


15+1

4+6

3+9

13+8


9+4

Total Publications

20
(+1)

9
(+6)

11
(+9)

20
(+8)


20(
+4)

(without Tech. Reports)

LIACC
-

March 2004

15

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Scientific production

1999

2000

2001

2002


2003


Prototypes (rev)

2(+3)

2+(2)

3+(1)

4+(2)


2+(4)


Conf. Org.+PCs



+4


+5

3+5

1+10


1+11


Ed.Boards


1

1

2

2


2


P.g.Courses+Inv. Sem.


2

3+4

1+4


7


Awards (prizes)

-

2

3

2


1+*


* Plus one nomination for the best paper at CIA’03

LIACC
-

March 2004

16

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

1.

Flexible and trustful tools and platforms for
agents interaction
:



Electronic Institutions for B2B



Automatic negotiation



Distributed Belief Revision



Main Research lines:

LIACC
-

March 2004

17

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Norms

&
Rules

links to
other
Institutions

V.O

dissolution


Q
-
Negotiation

V.O.

formation


Monitoring


V.O.

operation

financial

legal

MAgt

EAgt

EAgt

EAgt

Electronic


Contract

EAgt

1.

Flexible and trustful environments for agents interaction:

Ana Paula Rocha+ Henrique + Andreia+ ECO

Ontology
Services

LIACC
-

March 2004

18

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Protocols for both inter and intra coalition
negotiation for
Distributed Resources management


MACIV (MAS for Civil Construction)


Q
-
negotiation protocol
:


Multi
-
Attribute bid Evaluation


Qualitative feedback


Adaptive bid formation


Distributed dependencies resolution


FOREV implementation (V.E. formation platform)


Electronic Contracts
(in progress)


Ontology Services (in progress)


Negotiation and Electronic Institutions

ECO + JMFonseca
-
UNL

LIACC
-

March 2004

19

Distributed Artificial Intelligence
& Robotics Group

NIAD&R




Agent
-
based System for
EC

:




MAS architecture suitable for



B2C interaction



Agent
Tactics and Strategies

for Negotiation



Adaptive to the market dynamics (Q learning)



SMACE prototype available through the WEB

Henrique Cardoso + ECO


Time
-
dependent tactics


Anxious
0
1
Time
Utility
Linear
0
1
Time
Utility
Greedy

Time

Utility

0

1

LIACC
-

March 2004

20

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

JMFonseca + ECO

The winner !!!
D
I need
100
I can do 90
for 50
I can do 30
for 20
I can do
70 for 40
I can do
50 for 30
30 for 20
70 for 40
50 for 30
Need 100
Coalition formation
Four useful coalitions:
-
C
& D (cost=70)
-
B
& C (cost=60)
-
A
& C (cost=90)
-
A &
D
(cost=80)
Coalition team & best offer
announcing to coordinators
Task announcing
Intra
-
coalition negotiation
Quit
Leading
50
55
New best offer announcing to
coordinators
Leading
Quit
45
Leading
Task announcement & negotiation
The winner !!!
D
I need
100
I can do 90
for 50
I can do 30
for 20
I can do
70 for 40
I can do
50 for 30
30 for 20
70 for 40
50 for 30
Need 100
Coalition formation
Four useful coalitions:
-
C
& D (cost=70)
-
B
& C (cost=60)
-
A
& C (cost=90)
-
A &
D
(cost=80)
Coalition team & best offer
announcing to coordinators
Task announcing
Intra
-
coalition negotiation
Quit
Leading
50
55
New best offer announcing to
coordinators
Leading
Quit
45
Leading
Task announcement & negotiation
100
80
A
B
C
D
100
A
B
C
D
75%
100
A
B
C
D
OK
18
25
OK
100
A
B
C
D
64%
100
A
B
C
D
OK
7
100
A
B
C
D
62.5%
100
A
B
C
D
OK
Coalition configuration
Coordinator receives new
lower value and divulges
the lowering percentage
A and D OK but B and C
refuses
Coordinator proposes new
percentage to A and D
A OK but D refuses
Coordinator proposes new
percentage to A
A accepts
75
A
B
C
D
Coordinator sends new proposal
75
Initial costs
40
20
30
10
Intra
-
coalition negotiation
A
B
C
1
2
Coordinator 1
Coordinator 2
The self
-
depreciation problem
100
80
A
B
C
D
100
A
B
C
D
75%
100
A
B
C
D
OK
18
25
OK
100
A
B
C
D
64%
100
A
B
C
D
OK
7
100
A
B
C
D
62.5%
100
A
B
C
D
OK
Coalition configuration
Coordinator receives new
lower value and divulges
the lowering percentage
A and D OK but B and C
refuses
Coordinator proposes new
percentage to A and D
A OK but D refuses
Coordinator proposes new
percentage to A
A accepts
75
A
B
C
D
Coordinator sends new proposal
75
Initial costs
40
20
30
10
Intra
-
coalition negotiation
A
B
C
1
2
Coordinator 1
Coordinator 2
The self
-
depreciation problem
One software agent for each
physical resource ...
Edification
Garage
Storehouse
Planning
Personnel
Interconnecting network
Facilitator
Workers
Machinery
Workers
Supervisors
Chief
Stocks
manager
Facilitator
Edification
Personnel
Facilitator
Experts
Planning
Stocks
manager
Facilitator
Facilitator
Machinery
Storehouse
Garage
One software agent for each
physical resource ...
Edification
Garage
Storehouse
Planning
Personnel
Interconnecting network
Facilitator
Workers
Machinery
Workers
Supervisors
Chief
Stocks
manager
Facilitator
Edification
Personnel
Facilitator
Experts
Planning
Stocks
manager
Facilitator
Facilitator
Machinery
Storehouse
Garage
Edification
Garage
Storehouse
Planning
Personnel
Interconnecting network
Facilitator
Workers
Edification
Garage
Storehouse
Planning
Personnel
Interconnecting network
Facilitator
Workers
Machinery
Workers
Supervisors
Chief
Stocks
manager
Facilitator
Edification
Personnel
Machinery
Workers
Supervisors
Chief
Stocks
manager
Facilitator
Edification
Personnel
Facilitator
Facilitator
Experts
Planning
Stocks
manager
Facilitator
Facilitator
Machinery
Storehouse
Garage
Experts
Planning
Stocks
manager
Facilitator
Facilitator
Machinery
Storehouse
Garage
The winner !!!
D
I need
100
I can do 90
for 50
I can do 30
for 20
I can do
70 for 40
I can do
50 for 30
30 for 20
70 for 40
50 for 30
Need 100
Coalition formation
Four useful coalitions:
-
C
& D (cost=70)
-
B
& C (cost=60)
-
A
& C (cost=90)
-
A &
D
(cost=80)
Coalition team & best offer
announcing to coordinators
Task announcing
Intra
-
coalition negotiation
Quit
Leading
50
55
New best offer announcing to
coordinators
Leading
Quit
45
Leading
Task announcement & negotiation
The winner !!!
D
I need
100
I can do 90
for 50
I can do 30
for 20
I can do
70 for 40
I can do
50 for 30
30 for 20
70 for 40
50 for 30
Need 100
Coalition formation
Four useful coalitions:
-
C
& D (cost=70)
-
B
& C (cost=60)
-
A
& C (cost=90)
-
A &
D
(cost=80)
Coalition team & best offer
announcing to coordinators
Task announcing
Intra
-
coalition negotiation
Quit
Leading
50
55
New best offer announcing to
coordinators
Leading
Quit
45
Leading
Task announcement & negotiation
100
80
A
B
C
D
100
A
B
C
D
75%
100
A
B
C
D
OK
18
25
OK
100
A
B
C
D
64%
100
A
B
C
D
OK
7
100
A
B
C
D
62.5%
100
A
B
C
D
OK
Coalition configuration
Coordinator receives new
lower value and divulges
the lowering percentage
A and D OK but B and C
refuses
Coordinator proposes new
percentage to A and D
A OK but D refuses
Coordinator proposes new
percentage to A
A accepts
75
A
B
C
D
Coordinator sends new proposal
75
Initial costs
40
20
30
10
Intra
-
coalition negotiation
A
B
C
1
2
Coordinator 1
Coordinator 2
The self
-
depreciation problem
100
80
A
B
C
D
100
A
B
C
D
75%
100
A
B
C
D
OK
18
25
OK
100
A
B
C
D
64%
100
A
B
C
D
OK
7
100
A
B
C
D
62.5%
100
A
B
C
D
OK
Coalition configuration
Coordinator receives new
lower value and divulges
the lowering percentage
A and D OK but B and C
refuses
Coordinator proposes new
percentage to A and D
A OK but D refuses
Coordinator proposes new
percentage to A
A accepts
75
A
B
C
D
Coordinator sends new proposal
75
Initial costs
40
20
30
10
Intra
-
coalition negotiation
A
B
C
1
2
Coordinator 1
Coordinator 2
The self
-
depreciation problem
LIACC
-

March 2004

21

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Multi
-
agent systems dealing with
Conflict resolution




Argumentation
-
based

Belief Revision

in a Distributed
MAS involving a GIS



Application domain: DSS for Land use assessment



Prototype: DiPLoMAT System




available

M.Benedita Malheiro + ECO

LIACC
-

March 2004

22

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

C

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Expert System

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LIACC
-

March 2004

23

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

6. DOMÍNIO DE APLICAÇÃO

LIACC
-

March 2004

24

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

2.

Advanced features

for Autonomous Agents:


Agents and MAS
Learning
capabilities


Learning marketing strategies



“Emotion
-
based"

agents’ architectures




Main Research lines:

LIACC
-

March 2004

25

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

2.

Advanced features for Autonomous Agents:


Agents and MAS
Learning capabilities

Luis Nunes + ECO


“How can Heterogeneous Agents interactively learn and
“influence” each other in their learning process?”



Non
-
deterministic, partially observable, Non
-

supervised environment
-

Traffic Lights Control


LIACC
-

March 2004

26

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Luis Nunes + ECO


Traffic Light Control


Simulation based on real
data


Simplified car movement


1, 2 and 4 crossings
scenarios x 3 teams (
GA
,
QL
, Heuristic)


LIACC
-

March 2004

27

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Luis Nunes + ECO

Exchanging Advice

Use
communication

to
improve learning performance


Environments:

Multiple
agents dealing with
similar

problems

Agents use
different learning techniques



Expected features:

Improved resistance to local minima

No pre
-
selection of the
“best algorithm”

Group

performs better

than the best of its individuals



Learning
for Multi
-
Agent Systems:

LIACC
-

March 2004

28

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Advisee


Advisor


Environment

1. Observed
S
tate

2. Should I request advice ?

4.
S
tate (observed by the
A
dvisee)

3.To whom ?

5. Best guess is (a)

6. Advised action (a)

7. Integrate advice

8. Choose action and act

Sc
A

* P
A

< P
O

or ConfusedAbout(
S
tate)

T
A,Ar

* P
Ar
(S) > T
A,O

* P
O
(S)

Concepts
:

S
elf
-
c
onfidence

P
erformance

S
tate

T
rust

Actors
:

A
dvisee

A
dviso
r

O
ther agents

LIACC
-

March 2004

29

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



“Emotion
-
based“ agent architectures
:



based on neuro
-
science (cognition
-
emotion relationship)


“How to escape from traditional utility
-
based functions”?



Agents new features:
valence
-
based memory,


<V,I,E,G> associating Valence with



Goals and both internal and external sources

Relationships between

“emotion
-
like parameters”

Luis Sarmento + Daniel Moura+ECO

LIACC
-

March 2004

30

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Luis Sarmento + Daniel Moura+ECO


Emotional Elicitation


Process of evaluating the chances (V) of achieving a given
goal (G) upon the state of the environment (<E>) and the
agent internal state (<I>).


V = EEF
G
(<E>,<I>)



Emotion Accumulators


Enable to model emotions behavior through time (t);


Consumes a percentage (P
Input
) of an EEF
G
;


Value decays according to a decay constant (T
d
).


EA
G
(t,P
Input

,T
d
)



Basic Emotional Mechanism



EEF
G
(<E>,<I>)

EA
G
(t,P
Input

,T
d
)

LIACC
-

March 2004

31

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

3.

Coordination

of Agent
-
based teams




Coordination policies in adversarial environments



Main Research lines:

LIACC
-

March 2004

32

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



COACH UNILANG
:
general language to enable a special


agent ("coach") to supervise a team of co
-
operative robots.



agent
-
based
common framework

suitable for
controlling teams of cooperative robots (either
physical or simulated)


Techniques
: distinction between active and strategic
situations


Agents
Coordination

mechanisms: Situation
-
basedSP,
DPRExchange, ADVCOM, SLM, MM.


New team strategies (tactics, formations, player
types…)

Luis Paulo Reis

3.

Coordination

of Agent
-
based
teams


LIACC
-

March 2004

33

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Flexible Strategies

LIACC
-

March 2004

34

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Constraint Satisfaction

in a distributed environment
:



UNIPS
-

University Planning and Scheduling



to reach mutual agreement in distributed multi
-
agent system applications



UniLang: language for representing timetabling problems

Luis Paulo Reis

LIACC
-

March 2004

35

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

4.

Application

oriented:



Proof of “intelligent agent” concept in
specific application domains:



Elec. Market
, Mob.Comm.Networks,
Brokering
,


3D Visualisation, Traffic Control management…



Main Research lines:

LIACC
-

March 2004

36

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Intelligent
Brokering
for the Insurance domain (BeeGent)

LNogueira





ILP for Time Series Analysis. Optimal traffic control in
multi
-
class
packet switched networks


Alex Alves




MAS platform for
Electrical Energy e
-
Market

-

JLPinto



Agent
-
based framework making available
security
mechanisms

and negotiation algorithms tuned for this EE
-
market

4.

Application

oriented work:

LIACC
-

March 2004

37

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

2
-
BIAS (
B
rokerage in
I
nsurance


an
A
gent
-
based
S
ystem)

Customers

communities


Stereotypes


Negotiation


Ontology


Broker

CA

IA

IA

IA

Customer
description and
needs

Product
proposals

Interaction on
user’s behalf

Qualitative
feedback

Personalised
offers

...

Luis Nogueira+ECO

LIACC
-

March 2004

38

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Traffic Engineering of
Data CommunicationsNetwork


To assess the
adequacy of ILP for
Time Series Analysis
automation

Alex Alves+RC+ECO

VBR Traffic
50
55
60
65
70
75
80
85
90
1
6
11
16
21
26
31
36
41
46
51
56
61
66
71
76
81
86
91
96
Time
Load
observed
predicted
Time Series Forecasting

LIACC
-

March 2004

39

Distributed Artificial Intelligence
& Robotics Group

NIAD&R

Multi
-
agent Platform for Electricity


E
-
Market


Agents interaction using XML and
HTTPS (or SOAP?)


Intra
-
platform communications
with XML
-
RPC


Market Operator acts as a message
router; Auctions.


Agents
authenticate through digital
certificates


Messages between the Market
Operator and the Market Agents
are
digitally signed

Generator

Agent

Consum
er

Agent

Service

Provider

Agent

Market

Operator

Certificatio
n

Authority

Auctioneer

System

Operator

Database

System

Service

Provider

Platform

Service

Consumer

Agent

João Luis Pinto

LIACC
-

March 2004

40

Distributed Artificial Intelligence
& Robotics Group

NIAD&R




For the RoboCup
Simulation League



Agent
-
based control
Cameras deciding on
the best perspective
on the situation +
Director agent

Sérgio Louro+LPR+ECO




MAS for 3D visualisation of RoboCup games


LIACC
-

March 2004

41

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Deliberative agents responsible for
advising about the plan to be execute



Agent
-
based Robotics control
:




Hybrid layered architecture:



Reactive Agents for immediate action



1 PhD Thesis submitted and several papers produced



Learning basic competencies :


Simple neural networks,


Fuzzy rules

LIACC
-

March 2004

42

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Agent
-
based Robotics control
:

LIACC
-

March 2004

43

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Projects (1999
-
2001)



AVOEC: Agent
-
based platform for VE formation and
B2B EC


funding:FCT+FEDER
finished 2001




MACIV:Multi
-
Agent System for Distributed resource
management


funding:FCT+FEDER
finished 2000



AgentLink I (98
-
00) AMEC SIG

finished 2000


AgentLink II (00
-
02)

AMEC +ALAD SIGs




funding: European Union


FINESSE: Formalisation of Institutions and Norms for
Electronic Social Structures for Exchange


submitted



Inter
-
Network (EUNET, ILPNET, AgentLinkII) SIG on
"Agents that Learn, Adapt and Discover
funding:E.U.

LIACC
-

March 2004

44

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Projects (2002
-
2004)



LEMAS: Learning in MASystems in the RoboCup SLLeague

Funding: FCT+FEDER(03
-
04)



FCPortugal: New Coordination Methodologies applied to the
Simulation League




Funding: FCT+FEDER(03
-
04)



AgentLink III

AMEC +ALAD SIGs

Funding: European U. (03
-
)




PORTUS: A common framework for cooperation in Mobile
Robotics





Funding: FCT+FEDER(02
-
05)




OPEN: Open Platform for Enterprise Network


submitted to E.U.




LIACC
-

March 2004

45

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



International links



Member of the
Editorial Board of the AAMAS Journal

ed. Kluwer AP, (EO)



Member of the European Board of IOS Press and
Omsha Ltd “Frontiers in AI and Applications” Series for
European dissertations (EO)



Member of Technical Committee of the RoboCup
Simulation League (LPR)



Exchange

of students+researchers under Socrates
Program (U.Trier/G, Imperial College/UK, City
College/UK, ENM SaintEtienne/Fr)



Research
Evaluation

at Univ. J.Fourrier
-
Grenoble/Fr



“Coordination and Cooperation” in MAS Robo Cup
-
SIG

LIACC
-

March 2004

46

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



International links


DFKI
-
Germany

(KlausFisher, Mathias Klush)


Imperial College/Univ.London
(A.Mamdani)


Czech Technical University

(V.Marik, O.Stepankova)


U.Southampton
(N.Jennings, M.Luck)


Lab. Leibnitz
-

IMAG
(Dr. Y.Demazeau)


Univ. Utrecht (F.Dignum)


Université de Technologie de Compiègne
(J.P.Barthés)


École National des Mines Saint
-
Etienne (O.Boissier)


Institut Inteligencia Artificial, Barcelona (C.Sierra)


QMWC/U.London (N.Jennings)

LIACC
-

March 2004

47

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



International links


Univ. São Paulo (J.Sichman)


Pontifícia Univ. Católica Paraná
(M.Schmeil)


Univ. Bath (J.Padget)


Univ. Federal Rio Grande do Sul
(A.Bazzan)


Univ. of Trier/Germany
(N.Kuhn)


Xerox Research Centre in Europe, (J.M.Andreolli)


Achmea, Netherlands (V.Dignum)


LIACC
-

March 2004

48

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



National links



ISR Porto
(Dr.A.PMoreira, Dr. P.Costa)



CEMAS
-
C.Modelação e Análise Sistemas Ambientais
(Prof. P.Duarte)



I2S
-

Integrated Systems Software Company(A.Lhamas)



Guião (J.A.Alves)



Mota&Companhia (Civil Construction)



Univ. Beira Interior (DrªP.Prata)




Faculdade de Ciências Univ. Lisboa (Prof.H.Coelho)



Instituto Superior Técnico, U.T.Lisboa (Drª. A.Paiva)



FCT
-

Univ. Nova de Lisboa
(Prof. A.Garção)



IEETA
-

Univ. Aveiro
(Dr. L.Seabra Lopes, Dr. N.Lau)



INESCPorto
(Prof.M.Matos)

LIACC
-

March 2004

49

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Difficult to keep fruitful links with industry



Not enough publications in Journals



Robotics not enough attractive for software
people




EI and Agent
-
based
Negotiation

for EC and VO



Sophisticated
prototypes
have been released



Good results in competitions by using agent
-
based
team coordination



New research directions like
“emotion
-
based”
agents

and MAS
Learning



Weak points
:




Strong” points
:

LIACC
-

March 2004

50

Distributed Artificial Intelligence
& Robotics Group

NIAD&R



Future Directions:



More efforts on the
Applications
:



Adaptive Negotiation
Electricity e
-
Market



Simulation Tool for
fire
-
combat
training



Application of EI to a real
-
life domain



More efforts on:



Multi
-
agent Learning



Emotion
-
like Agents Architectures



General framework for
Electronic Institutions

including

Ontology related Services and Electronic
Contracts



To keep a fair balance between Research and Applications