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This book presents selected papers of 12 Workshops held in conjunction with the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019, in Macao, China, in August 2019. The workshops included in this volume are: AI4KM 2019: 7th International Workshop on Artificial Intelligence for Knowledge Management and Innovation. FinNLP 2019: First International Workshop on Financial Technology and Natural Language Processing. OR 2019: 32nd International Workshop on Qualitative Reasoning. SURL 2019: Second International Workshop on Scaling-Up Reinforcement Learning. First International Workshop on Bringing Semantic Knowledge into Vision and Text Understanding. EASyHAT 2019: First International Workshop on Evaluation of Adaptive Systems for Human-Autonomy Teaming. ACAN 2019: 12th International Workshop on Agent-based Complex Automated Negotiations. First International Workshop on Deep Learning for Human Activity Recognition. HAI 2019: Second International Workshop on Humanizing AI. International Workshop on Language Sense on Computer. AISafety 2019: International Workshop on Artificial Intelligence Safety. DeLBP 2019: 4th International Workshop on Declarative Learning Based Programming.

Artificial intelligence. --- Computers. --- Application software. --- Artificial Intelligence. --- Theory of Computation. --- Computing Milieux. --- Computer Applications. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- AI (Artificial intelligence) --- Artificial thinking --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Artificial intelligence --- Computer science. --- Computer and Information Systems Applications. --- Informatics --- Science

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Faults are a concern for Multi-Agent Systems (MAS) designers, especially if the MAS are built for industrial or military use because there must be some guarantee of dependability. Some fault classification exists for classical systems, and is used to define faults. When dependability is at stake, such fault classification may be used from the beginning of the system’s conception to define fault classes and specify which types of faults are expected. Thus, one may want to use fault classification for MAS; however, From Fault Classification to Fault Tolerance for Multi-Agent Systems argues that working with autonomous and proactive agents implies a special analysis of the faults potentially occurring in the system. Moreover, the field of Fault Tolerance (FT) provides numerous methods adapted to handle different kinds of faults. Some handling methods have been studied within the MAS domain, adapting to their specificities and capabilities but increasing the large amount of FT methods. Therefore, unless being an expert in fault tolerance, it is difficult to choose, evaluate or compare fault tolerance methods, preventing a lot of developed applications from not only to being more pleasant to use but, more importantly, from at least being tolerant to common faults. From Fault Classification to Fault Tolerance for Multi-Agent Systems shows that specification phase guidelines and fault handler studies can be derived from the fault classification extension made for MAS. From this perspective, fault classification can become a unifying concept between fault tolerance methods in MAS.

Artificial intelligence. --- Fault-tolerant computing. --- Multiagent systems. --- System safety. --- Mechanical Engineering --- Engineering & Applied Sciences --- Computer Science --- Mechanical Engineering - General --- Information Technology --- Artificial Intelligence --- Computing, Fault-tolerant --- Agent-based model (Computer software) --- MASs (Multiagent systems) --- Multi-agent systems --- Systems, Multiagent --- Computer science. --- Control engineering. --- Quality control. --- Reliability. --- Industrial safety. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Quality Control, Reliability, Safety and Risk. --- Control. --- Electronic data processing --- Electronic digital computers --- Fault tolerance (Engineering) --- Computer system failures --- Intelligent agents (Computer software) --- Reliability --- Artificial Intelligence. --- Control and Systems Theory. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Safety, System --- Safety of systems --- Systems safety --- Accidents --- Industrial safety --- Systems engineering --- Prevention --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Industrial accidents --- Industries --- Job safety --- Occupational hazards, Prevention of --- Occupational health and safety --- Occupational safety and health --- Prevention of industrial accidents --- Prevention of occupational hazards --- Safety, Industrial --- Safety engineering --- Safety measures --- Safety of workers --- System safety --- Dependability --- Trustworthiness --- Conduct of life --- Factory management --- Industrial engineering --- Reliability (Engineering) --- Sampling (Statistics) --- Standardization --- Quality assurance --- Quality of products

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Autonomous agents and multi-agent systems have grown into a promising technology offering a credible alternative for the design of intelligent and cooperative systems. Recently efforts have been made to provide novel tools, methods, and frameworks to establish the necessary standards for wider use of MAS as a technology of its own and not only as an attractive paradigm. This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Programming of the First International Workshop on Programming Multi-Agent Systems, PROMAS 2003, held in Melbourne, Australia in July 2003 as part of AAMAS 2003. Besides 8 workshop papers, the volume contains 3 invited papers to complete coverage of the relevant aspects. The papers are organized in topical sections on programming multi-agent systems, languages for multi-agent systems, and principles and tools for multi-agent systems.

Intelligent agents (Computer software) --- Computer programming --- Computer science. --- Computer communication systems. --- Software engineering. --- Programming languages (Electronic computers). --- Computer logic. --- Artificial intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Software Engineering. --- Computer Communication Networks. --- Logics and Meanings of Programs. --- Programming Languages, Compilers, Interpreters. --- 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 --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Computer science logic --- Logic, Symbolic and mathematical --- Computer languages --- Computer program languages --- Computer programming languages --- Machine language --- Languages, Artificial --- Computer software engineering --- Engineering --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Informatics --- Science --- Distributed processing --- Logic design. --- Artificial Intelligence. --- Design, Logic --- Design of logic systems --- Digital electronics --- Electronic circuit design --- Logic circuits --- Switching theory --- Intelligent agents (Computer software) - Congresses --- Computer programming - Congresses

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Programming --- Computer architecture. Operating systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- applicatiebeheer --- apps --- computers --- KI (kunstmatige intelligentie) --- architectuur (informatica)

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Faults are a concern for Multi-Agent Systems (MAS) designers, especially if the MAS are built for industrial or military use because there must be some guarantee of dependability. Some fault classification exists for classical systems, and is used to define faults. When dependability is at stake, such fault classification may be used from the beginning of the system’s conception to define fault classes and specify which types of faults are expected. Thus, one may want to use fault classification for MAS; however, From Fault Classification to Fault Tolerance for Multi-Agent Systems argues that working with autonomous and proactive agents implies a special analysis of the faults potentially occurring in the system. Moreover, the field of Fault Tolerance (FT) provides numerous methods adapted to handle different kinds of faults. Some handling methods have been studied within the MAS domain, adapting to their specificities and capabilities but increasing the large amount of FT methods. Therefore, unless being an expert in fault tolerance, it is difficult to choose, evaluate or compare fault tolerance methods, preventing a lot of developed applications from not only to being more pleasant to use but, more importantly, from at least being tolerant to common faults. From Fault Classification to Fault Tolerance for Multi-Agent Systems shows that specification phase guidelines and fault handler studies can be derived from the fault classification extension made for MAS. From this perspective, fault classification can become a unifying concept between fault tolerance methods in MAS.

Applied physical engineering --- Engineering sciences. Technology --- Production management --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- computers --- controleleer --- KI (kunstmatige intelligentie) --- kwaliteitscontrole --- ingenieurswetenschappen --- computerkunde --- robots