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The complexity of systems studied in distributed artificial intelligence (DAI), such as multi-agent systems, often makes it extremely difficult or even impossible to correctly and completely specify their behavioral repertoires and dynamics. There is broad agreement that such systems should be equipped with the ability to learn in order to improve their future performance autonomously. The interdisciplinary cooperation of researchers from DAI and machine learning (ML) has established a new and very active area of research and development enjoying steadily increasing attention from both communities. This state-of-the-art report documents current and ongoing developments in the area of learning in DAI systems. It is indispensable reading for anybody active in the area and will serve as a valuable source of information.

Machine learning --- Distributed artificial intelligence --- Computer Science --- Engineering & Applied Sciences --- 681.3*I2 <063> --- Learning, Machine --- Artificial intelligence --- Machine theory --- DAI (Artificial intelligence) --- Distributed AI (Artificial intelligence) --- Artificial intelligence. AI--Congressen --- 681.3*I2 <063> Artificial intelligence. AI--Congressen --- Computer science. --- Programming languages (Electronic computers). --- Artificial intelligence. --- Computer simulation. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Simulation and Modeling. --- Programming Languages, Compilers, Interpreters. --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Mathematical models --- Simulation methods --- Model-integrated computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Self-organizing systems --- Fifth generation computers --- Neural computers --- Computer languages --- Computer program languages --- Computer programming languages --- Machine language --- Languages, Artificial --- Informatics --- Science --- Congresses --- Artificial Intelligence. --- Machine learning - Congresses --- Distributed artificial intelligence - Congresses --- Programming languages (Electronic computers)

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681.3 --- Computerwetenschap --- 681.3* / / / / / / / / / / / / / / / / / / / / / / / / / / / / --- Expertsystemen [Elektronische informatieverwerking]. (Congres) --- Robotica. (Congres) --- Anleren. (Congres) --- Kennisleer. (Congres) --- Intelligence artificielle. (Congrès) --- Systèmes experts [Traitement automatique de l'information]. (Congrès) --- Robotique. (Congrès) --- Apprentissage. (Congrès) --- Connaissance (Théorie de la). (Congrès) --- Kunstmatig verstand. (Congres) --- Learning --- Expert System --- Vision --- Robotics --- Artificial intelligence --- Knowledge Representation --- Natural Language

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In the summer of 1956, John McCarthy organized the famous Dartmouth Conference which is commonly viewed as the founding event for the field of Artificial Intelligence. Knowledge Representation & Reasoning is traditionally strong in Europe and remains the biggest area of ECAI 2006.

Artificial intelligence --- Cybernetics --- E-books

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Artificial intelligence --- Proceedings --- Ecai