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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. OUTLINE. LIACC overview NIAD&R main Goals NIAD&R through Numbers.
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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
OUTLINE • LIACC overview • NIAD&R main Goals • NIAD&R through Numbers • 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
Advisory Committee Coordination Board general coordinator Scientific Board ~50% LIACC NCC F. Sciences ~23% NIAD&R F. Engineering University of Porto ~27% NIAAD F. Economics
LIACC • Existe desde 1988. • No fim de 2003 incluía: • 34 pessoas com doutoramento, • 40 outros membros (estudantes de doutoramento, bolseiros, etc.)
LIACC • 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); • 16capitulos de livros; • 133 outros artigos in actas de Congressos / Workshops • 9 actas de congressos ou Workshops editadas;
LIACC • (’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 • 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 • 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 • 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
NIAD&R Main Objectives: • To develop: • Models for inter-operability in Agent-based Systems • Agent-based Software for practical Applicationsin DDD • To help young researchers in preparing their thesis
Main Concept: • AGENTS : • Computational entities including the following features: • Distributed • Reactive and Communicative • Pro-Active • Autonomous • Other capabilities: • Mentalistic capabilities: • Beliefs, Desires, Intentions, Emotions • Multi-Agent Systems
Negotiation protocols Agents Interaction Coordination of teams of Agents Conflict resolution Learning and Adaptation Agent Capabilities Emotion-based agent architecture Electronic Institutions for VO Multiple-Experts DSS Agent Applications Simulation What is the rationale behind our research?
Nr. of Researchers 1999 2000 20012002 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 1120 21 Tech. _ _ _ _ _ Adm. ½ ½ ½ (shared) ½ (shared) ½ (shared)
Scientific production 1999 2000 20012002 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) 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 42 3 * Interview to TRN- Technical Research News Magazine
Scientific production1999 2000 20012002 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
Main Research lines: • Flexible and trustful tools and platforms for agents interaction: • Electronic Institutions for B2B • Automatic negotiation • Distributed Belief Revision
Ontology Services Electronic Contract legal financial EAgt MAgt EAgt EAgt EAgt Electronic Institution • Flexible and trustful environments for agents interaction: V.O. formation V.O. operation V.O dissolution Norms & Rules Q-Negotiation • Monitoring links to other Institutions Ana Paula Rocha+ Henrique + Andreia+ ECO
DEMO DEMO available available Finished • Negotiation and Electronic Institutions • 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) • Protocols for both inter and intra coalition negotiation for Distributed Resources management • MACIV (MAS for Civil Construction) ECO + JMFonseca-UNL
Time-dependent tactics Greedy available DEMO 1 Utility 0 Time • Agent-based System for EC : • MAS architecture suitable for • B2C interaction Finished • Agent Tactics and Strategies for Negotiation • Adaptive to the market dynamics (Q learning) • SMACE prototype available through the WEB Henrique Cardoso + ECO
available DEMO Finished JMFonseca + ECO
Argumentation-basedBelief Revision in a Distributed MAS involving a GIS • Application domain: DSS for Land use assessment • Prototype: DiPLoMAT System • available DEMO • Multi-agent systems dealing with Conflict resolution Finished M.Benedita Malheiro + ECO
C o o p e r a t i o n L a y e r A c q u a i n t a n c e S e l f M o d e l M o d e l C o m m u n i c a t i o n e M o d u l C o o p e r a t i o n M o d u l e C o o p e r a t i o n L a y e r A s s u m p t i o n b a s e d B e l i e f R e v i s i o n S y s t e m Expert System P r o b l e m S o l v e r A T M S K n o w l e d g e B a s e A s s u m p t i o n s F a c t s J u s t i f i c a t i o n s C o n s u m e r s B e l i e f s S c h e d u l e r I n f e r r e d N o d e s
6. DOMÍNIO DE APLICAÇÃO DiPLoMAT
Main Research lines: • Advanced features for Autonomous Agents: • Agents and MAS Learning capabilities • Learning marketing strategies • “Emotion-based" agents’ architectures
DEMO available • Advanced features for Autonomous Agents: • Agents and MAS Learning capabilities “How can Heterogeneous Agents interactively learn and “influence” each other in their learning process?” • Non-deterministic, partially observable, Non- supervised environment- Traffic Lights Control Luis Nunes + ECO
DEMO available • Traffic Light Control • Simulation based on real data • Simplified car movement • 1, 2 and 4 crossings scenarios x 3 teams (GA, QL, Heuristic) Luis Nunes + ECO
Exchanging Advice • Learning for Multi-Agent Systems: • 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 Luis Nunes + ECO
The process of advice-exchange 3.To whom ? Environment TA,Ar * PAr(S) > TA,O * PO(S) 7. Integrate advice Advisee 1. Observed State 4. State (observed by the Advisee) 8. Choose action and act Concepts: Self-confidence Performance State Trust Actors: Advisee Advisor Other agents 2. Should I request advice ? ScA * PA < PO or ConfusedAbout(State) 6. Advised action (a) Advisor 5. Best guess is (a)
DEMO available Relationships between “emotion-like parameters” • “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 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) Luis Sarmento + Daniel Moura+ECO
Main Research lines: • Coordination of Agent-based teams • Coordination policies in adversarial environments
DEMO available • Coordination of Agent-based teams • 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…) • COACH UNILANG: general language to enable a special agent ("coach") to supervise a team of co-operative robots. Luis Paulo Reis
Constraint Satisfactionin 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
Main Research lines: • Application oriented: • Proof of “intelligent agent” concept in specific application domains: • Elec. Market, Mob.Comm.Networks, Brokering, 3D Visualisation, Traffic Control management…
Application oriented work: • 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
Product proposals Interaction on user’s behalf Customer description and needs IA Broker CA IA Customers communities Stereotypes Negotiation Ontology DEMO ... available Qualitative feedback Personalised offers IA 2-BIAS (Brokerage in Insurance – an Agent-based System) Luis Nogueira+ECO
Traffic Engineering of Data CommunicationsNetwork Time Series Forecasting • To assess the adequacy of ILP for Time Series Analysis automation Alex Alves+RC+ECO
Certification Authority Database Auctioneer Market Operator System Operator System Service Provider Platform Service Consumer Agent Consumer Agent Service Provider Agent Generator Agent 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 João Luis Pinto
MAS for 3D visualisation of RoboCup games • For the RoboCup Simulation League • Agent-based control Cameras deciding on the best perspective on the situation + Director agent Sérgio Louro+LPR+ECO
Agent-based Robotics control: • Hybrid layered architecture: • Reactive Agents for immediate action Finished • Deliberative agents responsible for advising about the plan to be execute • Learning basic competencies : • Simple neural networks, • Fuzzy rules • 1 PhD Thesis submitted and several papers produced
Agent-based Robotics control: Finished
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.
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.
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
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)
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)
National links • 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) • 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)
Weak points: • “Strong” points: • 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
Future Directions: • More efforts on: • Multi-agent Learning • Emotion-like Agents Architectures • General framework for Electronic Institutions including Ontology related Services and Electronic Contracts • More efforts on the Applications: • Adaptive Negotiation Electricity e-Market • Simulation Tool for fire-combat training • Application of EI to a real-life domain • To keep a fair balance between Research and Applications