LIACC - March 2004 1 Distributed Artificial Intelligence & Robotics Group NIAD&R NIAD&R is a member...

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



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



NIAD&R

University of Porto

NCCF. Sciences

NIAADF. Economics

NIAD&RF. Engineering

ScientificBoard

Advisory Committee

Coordination Board

general coordinator

~50%

~23%

~27%



NIAD&R

Existe desde 1988.

No fim de 2003 incluía:34 pessoas com

doutoramento,40 outros membros

(estudantes de doutoramento, bolseiros, etc.)



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;



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.



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



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



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 DAModelling higher order concepts using ILPStatistical methods for classification. App. to the recognition of multi-spectral images and bioinformatics.

Data Mining for Text and Web



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:



NIAD&R

AGENTS : 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



NIAD&R

What is the rationale behind our research?

Agents Interaction

Negotiation protocolsCoordination of teams of AgentsConflict resolution

Agent Capabilities

Learning and Adaptation

Emotion-based agent architecture

Agent Applications

Electronic Institutions for VOMultiple-Experts DSSSimulation



NIAD&R

1999 2000 2001 2002 2003

Senior Res. 1 1 1 1 1PhDs 1 2 2+1-1 4 4

Res.Ass. 5 6 8-1 13 13Ext.Coll. 2 2 2 3 3TOTAL 9 12 11 20 21Tech. _ _ _ _ _Adm. ½ ½ ½ (shared) ½ (shared) ½ (shared)

Nr. of Researchers



NIAD&R

PhD Thesis approved 1 2 1(+1) 1 1MSc.Thesis approved 4 1 2 1 2Theses in prep(PhD+M) 4+4 3+8 5+6Total (Theses appr.) 5 3 4 2 3

* Interview to TRN- Technical Research News Magazine

Scientific production 1999 2000 2001 20022003

Chap. in Books 1 1 4 1Journ + Series 1+3 +4 1+3 2*+51+9Proceed +TRep 15+1 4+6 3+9 13+89+4Total Publications 20 (+1) 9 (+6) 11 (+9) 20(+8)

20(+4)(without Tech. Reports)



NIAD&R

Scientific production 1999 2000 2001 20022003

Prototypes (rev) 2(+3) 2+(2) 3+(1) 4+(2)2+(4)

Conf. Org.+PCs +4 +5 3+5 1+101+11

Ed.Boards 1 1 2 2 2

P.g.Courses+Inv. Sem. 2 3+4 1+47

Awards (prizes) - 2 3 2 1+*

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



NIAD&R

1. Flexible and trustful tools and platforms for agents interaction: Electronic Institutions for B2B Automatic negotiation Distributed Belief Revision

Main Research lines:



NIAD&R

Norms & Rules

links to other

Institutions

V.O

dissolution

Q-Negotiation

V.O. formation

Monitoring

V.O.operation

financiallegal

MAgt

EAgt

EAgt

EAgtElectronic Contract

EAgt

1. Flexible and trustful environments for agents interaction:

Ana Paula Rocha+ Henrique + Andreia+ ECO

Electronic Instit

ution

Ontology Services



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

available

ECO + JMFonseca-UNL

available

Finished



NIAD&R

available

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

Finish

ed

Henrique Cardoso + ECO

Time-dependent tactics

Anxious

0

1

Time

Util

ity

Linear

0

1

Time

Util

ity

Greedy

Time

Uti

lity

0

1



NIAD&R

available

Finish

ed

JMFonseca + ECO

The winner !!!

D

I need100 I can do 90

for 50

I can do 30for 20

I can do70 for 40

I can do50 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 offerannouncing to coordinators

Task announcing

Intra-coalition negotiationQuit Leading50 55

New best offer announcing tocoordinatorsLeading

Quit

45

Leading

Task announcement & negotiation

The winner !!!

D

I need100 I can do 90

for 50

I can do 30for 20

I can do70 for 40

I can do50 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 offerannouncing to coordinators

Task announcing

Intra-coalition negotiationQuit Leading50 55

New best offer announcing tocoordinatorsLeading

Quit

45

Leading

Task announcement & negotiation

One software agent for eachphysical resource ...

EdificationGarageStorehousePlanningPersonnelInterconnecting network

Facilitator

Workers

Machinery

Workers

Supervisors

Chief

Stocksmanager

Facilitator

Edification

Personnel

FacilitatorExperts

Planning

Stocksmanager

Facilitator

Facilitator

Machinery

Storehouse

Garage

One software agent for eachphysical resource ...


Facilitator

Workers

Machinery

Workers

Supervisors

Chief

Stocksmanager

Facilitator

Edification

Personnel

FacilitatorExperts

Planning

Stocksmanager

Facilitator

Facilitator

Machinery

Storehouse

Garage


Facilitator

Workers


Facilitator

Workers

Machinery

Workers

Supervisors

Chief

Stocksmanager

Facilitator

Edification

Personnel

Machinery

Workers

Supervisors

Chief

Stocksmanager

Facilitator

Edification

Personnel

FacilitatorFacilitatorExperts

Planning

Stocksmanager

Facilitator

Facilitator

Machinery

Storehouse

Garage

Experts

Planning

Stocksmanager

Facilitator

Facilitator

Machinery

Storehouse

Garage 100

80

A B C D

100

A B C D

75% 100

A B C DOK

18 25OK

100

A B C D

64% 100

A B C DOK 7

100

A B C D

62.5%

100

A B C D

OK

Coalition configurationCoordinator receives newlower value and divulgesthe lowering percentage

A and D OK but B and Crefuses

Coordinator proposes newpercentage to A and D

A OK but D refuses Coordinator proposes newpercentage to A

A accepts

75

A B C DCoordinator sends new proposal

75

Initial costs

40 20 30 10

Intra-coalition negotiation

AB

C

12

Coordinator 1

Coordinator 2

The self-depreciation problem

100

80

A B C D

100

A B C D

75% 100

A B C DOK

18 25OK

100

A B C D

64% 100

A B C DOK 7

100

A B C D

62.5%

100

A B C D

OK

Coalition configurationCoordinator receives newlower value and divulgesthe lowering percentage

A and D OK but B and Crefuses

Coordinator proposes newpercentage to A and D

A OK but D refuses Coordinator proposes newpercentage to A

A accepts

75

A B C DCoordinator sends new proposal

75

Initial costs

40 20 30 10

Intra-coalition negotiation

AB

C

12

Coordinator 1

Coordinator 2

The self-depreciation problem



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

Finish

ed

M.Benedita Malheiro + ECO



NIAD&R

Cooperation Layer

Expert System

Self Model AcquaintanceModel

CommunicationModule

Cooperation Module

Cooperation Layer

Problem Solver

Knowledge Base

Scheduler

Facts

Consumers

ATMS

Assumptions

Inferred Nodes

Justifications

Beliefs

Assumption based Belief Revision System



NIAD&R

6. DOMÍNIO DE APLICAÇÃO6. DOMÍNIO DE APLICAÇÃO

DiPLoMAT



NIAD&R

2. Advanced features for Autonomous Agents: Agents and MAS Learning capabilities Learning marketing strategies “Emotion-based" agents’ architectures




NIAD&R

2. Advanced features for Autonomous Agents:

Agents and MAS Learning capabilities

Luis Nunes + ECO

available

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

Non-deterministic, partially observable, Non- supervised environment- Traffic Lights Control



NIAD&R

Luis Nunes + ECO

available

• Traffic Light Control• Simulation based on real

data • Simplified car movement• 1, 2 and 4 crossings

scenarios x 3 teams (GA, QL, Heuristic)



NIAD&R

Luis Nunes + ECO

Exchanging Advice

Use communication to improve learning performance• Environments:

Multiple agents dealing with similar problemsAgents use different learning techniques

• Expected features:Improved resistance to local minimaNo pre-selection of the “best algorithm”Group performs better than the best of its individuals

Learning for Multi-Agent Systems:



NIAD&R

The process of advice-exchange

Advisee

Advisor

Environment

1. Observed State

2. Should I request advice ?

4. State (observed by the Advisee)

3.To whom ?

5. Best guess is (a)

6. Advised action (a)

7. Integrate advice

8. Choose action and act

ScA * PA < PO or ConfusedAbout(State)

TA,Ar * PAr(S) > TA,O * PO(S)

Concepts:Self-confidencePerformanceStateTrustActors:AdviseeAdvisorOther agents



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

available



NIAD&R

Luis Sarmento + Daniel Moura+ECO

The Emotional Mechanism

• 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 = EEFG(<E>,<I>)

• Emotion Accumulators– Enable to model emotions behavior through time (t);– Consumes a percentage (PInput) of an EEFG;– Value decays according to a decay constant (Td).

EAG(t,PInput ,Td)

• Basic Emotional Mechanism

EEFG(<E>,<I>) EAG(t,PInput ,Td)



NIAD&R

3. Coordination of Agent-based teams

Coordination policies in adversarial environments




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

available

3. Coordination of Agent-based teams



NIAD&R

Flexible Strategies



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



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…




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:



NIAD&R

2-BIAS (Brokerage in Insurance – an Agent-based System)

Customerscommunities

Stereotypes

Negotiation

Ontology

Broker

CA

IA

IA

IA

Customer description and

needs

Product proposalsInteraction on

user’s behalf

Qualitative feedbackPersonalised

offers

...

Luis Nogueira+ECOavailable



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

Lo

ad

observed

predicted

Time Series Forecasting



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

GeneratorAgent

Consumer

Agent

ServiceProvider

Agent

MarketOperator

Certification

Authority

Auctioneer

SystemOperator

Database

SystemServiceProvider

Platform

ServiceConsumer

Agent

João Luis Pinto



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



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

Finish

ed



NIAD&R

Agent-based Robotics control:

Finish

ed



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 2000AgentLink II (00-02) AMEC +ALAD SIGs

funding: European UnionFINESSE: 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.



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.



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



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)



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)



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)



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” agentsand MAS Learning

Weak points:

“Strong” points:



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 includingOntology related Services and Electronic Contracts

To keep a fair balance between Research and Applications

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LIACC - March 2004 1 Distributed Artificial Intelligence & Robotics Group NIAD&R NIAD&R is a member...

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