[ES]Hasta el momento no se conocen modelos de tiempo real especificamente desarrollados para su uso en sistemas abiertos, como las Organizaciones Virtuales de Agentes (OVs). Convencionalmente, los modelos de tiempo real se aplican a sistemas cerrados donde todas las variables se conocen a priori. Esta tesis presenta nuevas contribuciones y la novedosa integracion de agentes en tiempo real dentro de OVs. Hasta donde alcanza nuestro conocimiento, este es el primer modelo especificamente disenado para su aplicacion en OVs con restricciones temporales estrictas. Esta tesis proporciona una nueva perspectiva que combina la apertura y dinamicidad necesarias en una OV con las restricciones de tiempo real. Esto es una aspecto complicado ya que el primer paradigma no es estricto, como el propio termino de sistema abierto indica, sin embargo, el segundo paradigma debe cumplir estrictas restricciones. En resumen, el modelo que se presenta permite definir las acciones que una OV debe llevar a cabo con un plazo concreto, considerando los cambios que pueden ocurrir durante la ejecucion de un plan particular. Es una planificacion de tiempo real en una OV. Otra de las principales contribuciones de esta tesis es un modelo para el calculo del tiempo de ejecucion en el peor caso (WCET). La propuesta es un modelo efectivo para calcular el peor escenario cuando un agente desea formar parte de una OV y para ello, debe incluir sus tareas o comportamientos dentro del sistema de tiempo real, es decir, se calcula el WCET de comportamientos emergentes en tiempo de ejecucion. Tambien se incluye una planificacion local para cada nodo de ejecucion basada en el algoritmo FPS y una distribucion de tareas entre los nodos disponibles en el sistema. Para ambos modelos se usan modelos matematicos y estadisticos avanzados para crear un mecanismo adaptable, robusto y eficiente para agentes inteligentes en OVs. El desconocimiento, pese al estudio realizado, de una plataforma para sistemas abiertos que soporte agentes con restricciones de tiempo real y los mecanismos necesarios para el control y la gestion de OVs, es la principal motivacion para el desarrollo de la plataforma de agentes PANGEA+RT. PANGEA+RT es una innovadora plataforma multi-agente que proporciona soporte para la ejecucion de agentes en ambientes de tiempo real. Finalmente, se presenta un caso de estudio donde robots heterogeneos colaboran para realizar tareas de vigilancia. El caso de estudio se ha desarrollado con la plataforma PANGEA+RT donde el modelo propuesto esta integrado. Por tanto al final de la tesis, con este caso de estudio se obtienen los resultados y conclusiones que validan el modelo.

Model for WCET prediction, scheduling and task allocation for emergent agent-behaviours in real-time scenarios

This report investigates JACK Intelligent Agents and JACK Teams, and makes a comparison between the two. The main object was to find indications that point out which modeling paradigm that results in least development effort, and which one that is creating the most feasible platform regarding teamwork construction. The application domain is decision-support systems used in oil production. The aspects evaluated are development effort, degree of coupling, encapsulation of functionality, abstraction level, delegation of autonomy, and scalability. The solutions developed in the comparison had static team formations that included few teammembers. This caused less development effort by using JACK Intelligent Agents, and was the main reason why it was considerate to be the preferred modeling paradigm in this case. This was partly experienced because reasoning based on the actual team membership was not used in the JACK Teams version. The use of roles was used instead, causing more JACK entities where it could have been avoided. Dynamic team formations during runtime were not needed due to the reference problem introduced. Maintaince during runtime, for instance introducing new subteams and changing the role structure was not looked into. Introducing teams in large scale was not performed. These four factors could have caused a different result. The question is if JACK Teams shows its potential through the oil production system designed in this report.

A Comparison between JACK Intelligent Agents and JACK Teams Applied in Teamwork

Traditional approaches for software agents to represent interaction protocols in open systems, such as FSM, Petri-Nets and AUML result in rigid and heavily constrained protocols. This is due to the fact that the resulting protocols contain only legal sequences of actions. However, in an open and uncertain environment, protocols need to be flexible so as to handle different scenarios that might occur. The development of the Commitment Machine framework allows for flexible specification of protocols. It defines a high level concept of using commitments to govern the execution of agent actions. This is done by attaching meaningful content to each protocol state and action, instead of representing them as just state transitions or message exchange. Previous work represent and implement the commitment machine framework using the Event Calculus, by supplying the specified commitment machine protocol to an event calculus planner, which then works out the alternative protocol runs. However, the generated protocol runs are only available for reference but not for execution. This is because the protocol runs are not integrated with the agents involved. The outcome of this project is to enable the successful execution of the commitment framework by agents. This is done by integrating the CM reasoning framework with JACK Intelligent Agent Language for automatic protocol generation and execution. Two approaches were taken for the implementation and compared: JACK Agents method and JACK Teams Method. As a result of the comparison, JACK Teams prove to be a better method of implementation as its framework is more suitable for the realization of commitment machine protocols.

Yeo Huang-Yu Daren

Papers

Automatic Protocol Generation Based on Commitment Machines