A FORMALIZATION FOR MULTI-AGENT DECISION SUPPORT IN COOPERATIVE ENVIRONMENTS. A FRAMEWORK FOR SITUATED AGENTS

La tesis propone un marco de trabajo para el soporte de la toma de decisiones adecuado para soportar la ejecucion distribuida de acciones cooperativas en entornos multi-agente dinamicos y complejos. Soporte para la toma de decisiones es un proceso que intenta mejorar la ejecucion de la toma de decisiones en escenarios cooperativos. Este proceso ocurre continuamente en la vida diaria. Los humanos, por ejemplo, deben tomar decisiones acerca de que ropa usar, que comida comer, etc. En este sentido, un agente es definido como cualquier cosa que esta situada en un entorno y que actua, basado en su observacion, su interpretacion y su conocimiento acerca de su situacion en tal entorno para lograr una accion en particular.Por lo tanto, para tomar decisiones, los agentes deben considerar el conocimiento que les permita ser consientes en que acciones pueden o no ejecutar. Aqui, tal proceso toma en cuenta tres parametros de informacion con la intencion de personificar a un agente en un entorno tipicamente fisico. Asi, el mencionado conjunto de informacion es conocido como ejes de decision, los cuales deben ser tomados por los agentes para decidir si pueden ejecutar correctamente una tarea propuesta por otro agente o humano. Los agentes, por lo tanto, pueden hacer mejores decisiones considerando y representando apropiadamente tal informacion. Los ejes de decision, principalmente basados en: las condiciones ambientales, el conocimiento fisico y el valor de confianza del agente, provee a los sistemas multi-agente un confiable razonamiento para alcanzar un factible y exitoso rendimiento cooperativo.Actualmente, muchos investigadores tienden a generar nuevos avances en la tecnologia agente para incrementar la inteligencia, autonomia, comunicacion y auto-adaptacion en escenarios agentes tipicamente abierto y distribuidos. En este sentido, esta investigacion intenta contribuir en el desarrollo de un nuevo metodo que impacte tanto en las decisiones individuales como colectivas de los sistemas multi-agente. Por lo tanto, el marco de trabajo propuesto ha sido utilizado para implementar las acciones concretas involucradas en el campo de pruebas del futbol robotico. Este campo emula los juegos de futbol real, donde los agentes deben coordinarse, interactuar y cooperar entre ellos para solucionar tareas complejas dentro de un escenario dinamicamente cambiante y competitivo, tanto para manejar el diseno de los requerimientos involucrados en las tareas como para demostrar su efectividad en trabajos colectivos. Es asi que los resultados obtenidos tanto en el simulador como en el campo real de experimentacion, muestran que el marco de trabajo para el soporte de decisiones propuesto para agentes situados es capaz de mejorar la interaccion y la comunicacion, reflejando en un adecuad y confiable trabajo en equipo dentro de entornos impredecibles, dinamicos y competitivos. Ademas, los experimentos y resultados tambien muestran que la informacion seleccionada para generar los ejes de decision para situar a los agentes, es util cuando tales agentes deben ejecutar una accion o hacer un compromiso en cada momento con la intencion de cumplir exitosamente un objetivo colectivo. Finalmente, algunas conclusiones enfatizando las ventajas y utilidades del trabajo propuesto en la mejora del rendimiento colectivo de los sistemas multi-agente en situaciones tales como tareas coordinadas y asignacion de tareas son presentadas.

[1]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[2]  Liping Sui.  Decision support systems based on knowledge management , 2005, Proceedings of ICSSSM '05. 2005 International Conference on Services Systems and Services Management, 2005..

[3]  Marc Esteva,et al.  On the formal specification of electronic institutions , 2001 .

[4]  Peter Stone,et al.  Layered learning in multiagent systems - a winning approach to robotic soccer , 2000, Intelligent robotics and autonomous agents.

[5]  Peter Stone,et al.  CMUnited: a team of robotics soccer agents collaborating in an adversarial environment , 1998, CROS.

[6]  Gaurav S. Sukhatme,et al.  Emergent Robot Differentiation for Distributed Multi-Robot Task Allocation , 2004, DARS.

[7]  Daniel J. Power,et al.  Web-Based and Model-Driven Decision Support Systems: Concepts and Issues , 2000 .

[8]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[9]  Thomas G. Dietterich,et al.  A Multi-agent Architecture Integrating Learning and Fuzzy Techniques for Landmark-Based Robot Navigation , 2002, CCIA.

[10]  Brian R. Duffy,et al.  Robots Social Embodiment in Autonomous Mobile Robotics , 2004 .

[11]  Hisamichi Toyoshima,et al.  Quantitative evaluation of communication traffic of mobile agents in distributed constraint satisfaction model , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[12]  A. Adla,et al.  A Cooperative Intelligent Decision Support System , 2006, 2006 International Conference on Service Systems and Service Management.

[13]  Maja J. Mataric,et al.  Multi-robot task allocation: analyzing the complexity and optimality of key architectures , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[14]  J. V. Rauff,et al.  Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence , 2005 .

[15]  Ali A. Ghorbani,et al.  Value centric trust in multiagent systems , 2003, Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003).

[16]  Victor R. Lesser,et al.  Cooperative Multiagent Systems: A Personal View of the State of the Art , 1999, IEEE Trans. Knowl. Data Eng..

[17]  Reid G. Simmons,et al.  First Results in the Coordination of Heterogeneous Robots for Large-Scale Assembly , 2000, ISER.

[18]  Michael Wooldridge,et al.  Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence , 1999 .

[19]  Gaurav S. Sukhatme,et al.  Multi-Robot Task Allocation in Uncertain Environments , 2003, Auton. Robots.

[20]  A. Roadmapof.  A Roadmap of Agent Research and Development , 1995 .

[21]  Les Gasser,et al.  Research Directions for Service-Oriented Multiagent Systems , 2005, IEEE Internet Comput..

[22]  Robert W. Brennan,et al.  Holonic job shop scheduling using a multiagent system , 2005, IEEE Intelligent Systems.

[23]  Michael Luck,et al.  Understanding Agent Systems , 2001, Springer Series on Agent Technology.

[24]  Lynne E. Parker,et al.  Current State of the Art in Distributed Autonomous Mobile Robotics , 2000 .

[25]  Josep Vehí,et al.  Studies about the atomic capabilities concept for linear control systems in physical multi-agent environments , 2005, 2005 International Symposium on Computational Intelligence in Robotics and Automation.

[26]  Jacques Ferber,et al.  Multi-agent systems - an introduction to distributed artificial intelligence , 1999 .

[27]  Guangjun Liu,et al.  Development of Control System Architecture for Modular and Re-configurable Robot Manipulators , 2007, 2007 International Conference on Mechatronics and Automation.

[28]  Vijay Kumar,et al.  An architecture for tightly coupled multi-robot cooperation , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[29]  M. Brinn,et al.  A Framework for Multiresolutional Knowledge Dissemination and Collection in Dynamic Agent Societies , 2007, 2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems.

[30]  Y. Shoham.  Introduction to Multi-Agent Systems , 2002 .

[31]  Kian Hsiang Low,et al.  A hybrid mobile robot architecture with integrated planning and control , 2002, AAMAS '02.

[32]  Paul Levi,et al.  Cooperative Agent Behavior Based on Special Interaction Nets , 2006, IAS.

[33]  M. Unel,et al.  Coordinated task manipulation by nonholonomic mobile robots , 2006, 9th IEEE International Workshop on Advanced Motion Control, 2006..

[34]  Enrique González,et al.  AOPOA - Organizational Approach for Agent Oriented Programming , 2006, ICEIS.

[35]  Gerhard Weiss,et al.  Multiagent Systems , 1999 .

[36]  Maurizio Porfiri,et al.  Agreement over networks of mobile agents , 2007, 2007 46th IEEE Conference on Decision and Control.

[37]  Nicholas R. Jennings,et al.  Agent-based control systems , 2003 .

[38]  R. A. Brooks,et al.  Intelligence without Representation , 1991, Artif. Intell..

[39]  Behrouz Homayoun Far,et al.  A Negotiation Model for Large Scale Multi-Agent Systems , 2006, 2006 IEEE International Conference on Information Reuse & Integration.

[40]  Stephen P. Boyd,et al.  Future directions in control in an information-rich world , 2003 .

[41]  Efraim Turban,et al.  Decision Support and Expert Systems: Management Support Systems , 1990 .

[42]  Sarvapali D. Ramchurn,et al.  Trust in Multiagent Systems , 2004 .

[43]  Yuxiang Wu,et al.  A Decision Support System for Filtering and Analysis of Carbon Dioxide Capture Data , 2007, 2007 Canadian Conference on Electrical and Computer Engineering.

[44]  Sean Luke,et al.  Cooperative Multi-Agent Learning: The State of the Art , 2005, Autonomous Agents and Multi-Agent Systems.

[45]  Maja J. Matarić,et al.  Robust Behavior-Based Control for Distributed Multi-Robot Collection Tasks , 2000 .

[46]  Naga K Krothapalli.  Dynamic task allocation in multi-agent systems , 2003 .

[47]  Jeremy V. Pitt,et al.  A real-time architecture for time-aware agents , 2004, IEEE Trans. Syst. Man Cybern. Part B.

[48]  Michael Luck,et al.  Agent technology, Computing as Interaction , 2005 .

[49]  Josep Vehí,et al.  Self-knowledge based on the atomic capabilities concept - a perspective to achieve sure commitments among physical agents , 2005, ICINCO.

[50]  Paul Scerri,et al.  Comparing Three Approaches to Large-Scale Coordination , 2006 .

[51]  Angela Davids,et al.  Urban Search and Rescue Robots: From Tragedy to Technology , 2002, IEEE Intell. Syst..

[52]  Yong Sun,et al.  Agent Hybrid Architecture and Its Decision Processes , 2006, 2006 International Conference on Machine Learning and Cybernetics.

[53]  Aiguo Song,et al.  Hybrid Behavior Coordination Mechanism for Navigation of Reconnaissance Robot , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[54]  A. Jain,et al.  Simulation to Evaluate Autonomous Behaviors for Mobile Planetary Surface Science Missions , 2007, 2007 IEEE Aerospace Conference.

[55]  Maja J. Mataric,et al.  Sold!: auction methods for multirobot coordination , 2002, IEEE Trans. Robotics Autom..

[56]  Nikolay Mehandjiev,et al.  Agent Interaction Protocols and Flexible Agent Interaction in Dynamic Environments , 2006, 15th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE'06).

[57]  Gaurav S. Sukhatme,et al.  Multi-robot task allocation in the light of uncertainty , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[58]  Lynne E. Parker,et al.  Robot Teams: From Diversity to Polymorphism , 2002 .

[59]  Lynne E. Parker,et al.  Lifelong Adaptation in Heterogeneous Multi-Robot Teams: Response to Continual Variation in Individual Robot Performance , 2000, Auton. Robots.

[60]  Robin R. Murphy,et al.  Human-robot interaction in rescue robotics , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[61]  Michael Luck,et al.  Agent technology: Enabling next generation computing , 2003 .

[62]  Danny Weyns,et al.  Towards commitments for situated agents , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[63]  Pat Langley.  An adaptive architecture for physical agents , 2005 .

[64]  Rino Falcone,et al.  Why a cognitive trustier performs better: simulating trustbased Contract Nets , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[65]  Quintero Monroy,et al.  Introspection on control-grounded capabilities. An agent inspired approach for control , 2007 .

[66]  Alexander Zelinsky,et al.  An architecture for distributed cooperative planning in a behaviour-based multi-robot system , 1999, Robotics Auton. Syst..

[67]  Albert Oller Pujol.  Disseny d'agents físics: inclusió de capacitats específiques per a l'avaluació de l'eficiència d'accions , 2003 .

[68]  Maja J. Mataric,et al.  Principled Communication for Dynamic Multi-robot Task Allocation , 2000, ISER.

[69]  Qinghai Miao,et al.  Modeling and analysis of artificial transportation system based on multi-agent technology , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[70]  Munindar P. Singh,et al.  Resolving Commitments among Autonomous Agents , 2003, Workshop on Agent Communication Languages.

[71]  Nikos Vlassis,et al.  A Concise Introduction to Multiagent Systems and Distributed AI , 2003 .

[72]  Ayanna M. Howard,et al.  A methodology to assess performance of human-robotic systems in achievement of collective tasks , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[73]  Nicholas R. Jennings,et al.  Agent-based control systems: Why are they suited to engineering complex systems? , 2003 .

[74]  B.H. Far,et al.  A collective view and methodologies for software agents' interaction , 2004, Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513).

[75]  Juan Antonio Rodríguez-Aguilar,et al.  On the design and construction of agent-mediated institutions , 2001 .

[76]  NICHOLAS R. JENNINGS,et al.  An agent-based approach for building complex software systems , 2001, CACM.

[77]  Nicholas R. Jennings,et al.  On agent-based software engineering , 2000, Artif. Intell..

[78]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[79]  Sven Behnke,et al.  A Hierarchy of Reactive Behaviors Handles Complexity , 2000, Balancing Reactivity and Social Deliberation in Multi-Agent Systems.

[80]  Jong-Hwan Kim,et al.  Hybrid Architecture for Kick Motion of Small-sized Humanoid Robot, HanSaRam-VI , 2006, 2006 SICE-ICASE International Joint Conference.

[81]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[82]  Manuela M. Veloso,et al.  Multiagent Systems: A Survey from a Machine Learning Perspective , 2000, Auton. Robots.

[83]  Lynne E. Parker,et al.  Editorial: Advances in Multi-Robot Systems , 2002 .

[84]  Efraim Turban,et al.  Decision Support Systems and Intelligent Systems (7th Edition) , 2004 .

[85]  Marcelo Luis Errecalde,et al.  Agentes y sistemas multiagente , 2004 .

[86]  Lynne E. Parker,et al.  A Complete Methodology for Generating Multi-Robot Task Solutions using ASyMTRe-D and Market-Based Task Allocation , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[87]  Majid Nili Ahmadabadi,et al.  Behavior hierarchy learning in a behavior-based system using reinforcement learning , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[88]  Lu Xu,et al.  The Mobile Robot Navigation in Dynamic Environment , 2007, 2007 International Conference on Machine Learning and Cybernetics.

[89]  Anand S. Rao,et al.  BDI Agents: From Theory to Practice , 1995, ICMAS.

[90]  Vicente Matellán Olivera,et al.  ABC2 an Agenda Based Multi-Agent Model for Robots Control and Cooperation , 2001, J. Intell. Robotic Syst..

[91]  Ansgar Bredenfeld,et al.  Team Cooperation Using Dual Dynamics , 2000, Balancing Reactivity and Social Deliberation in Multi-Agent Systems.

[92]  Lynne E. Parker.  Cooperative Robot Teams Applied to the Site Preparation Task , 2001 .

[93]  Nicholas R. Jennings,et al.  Coordination through Joint Intentions in Industrial Multiagent Systems , 1993, AI Mag..

[94]  P. Finlay.  Introducing Decision Support Systems , 1994 .

[95]  Lynne E. Parker,et al.  Distributed Intelligence: Overview of the Field and Its Application in Multi-Robot Systems , 2008, AAAI Fall Symposium: Regarding the Intelligence in Distributed Intelligent Systems.

[96]  Hector J. Levesque,et al.  Intention is Choice with Commitment , 1990, Artif. Intell..

[97]  Daniele Nardi,et al.  Coordination among heterogeneous robotic soccer players , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[98]  Timothy W. Finin,et al.  KQML as an agent communication language , 1994, CIKM '94.

[99]  Kevin Crowston,et al.  The interdisciplinary study of coordination , 1994, CSUR.

[100]  Roberto Gorrieri,et al.  Coordination Models: A Guided Tour , 2001, Coordination of Internet Agents: Models, Technologies, and Applications.

[101]  K. Sycara,et al.  This Is a Publication of the American Association for Artificial Intelligence Multiagent Systems Multiagent System Issues and Challenges Individual Agent Reasoning Task Allocation Multiagent Planning Recognizing and Resolving Conflicts Managing Communication Modeling Other Agents Managing Resources , 2022 .

[102]  E. Gonzalez,et al.  MRCC: A Multi-Resolution Cooperative Control Agent Architecture , 2007, 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07).

[103]  Jordan B. Pollack,et al.  Embodied Evolution: Distributing an evolutionary algorithm in a population of robots , 2002, Robotics Auton. Syst..