Programming Service Oriented Agents

This paper introduces a programming language for service-oriented agents. JADL++ combines the ease of use of scripting-languages with a state-of-the-art service oriented approach which allows the seamless integration of web-services. Furthermore, the language includes OWL-based ontologies for semantic descriptions of data and services, thus allowing agents to make intelligent decisions about service calls

Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review

Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computerscientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI” – in particular, logic-based ones will take place in the next few years. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones

Towards a simulation interoperability framework between an agent-based simulator and a BPMN engine using REST protocol

O paradigma atual de um modelo de processo de negócio é que é uma representação de uma sequência de tarefas que atuam sobre um “input” de dados, para produzir uma “output”, visando a produção de um novo serviço ou produto. Embora esta seja uma forma válida de interpretar um processo de negócio, ela não considera em pormenor a influência de fenómenos externos, por exemplo, comportamento humano, comunicação, interações sociais, a cultura organizacional que pode ter um efeito significativo na eficiência um processo de negócio. Como a dinâmica destes fenómenos externos não é linear, eles podem ser interpretados como um sistema complexo, que são sistemas que se comportam de tal forma que não podem ser explicados simplesmente olhando para o comportamento das suas partes individuais. Esta forma holística de pensar sobre os processos de negócio abre as portas à possibilidade de combinar diferentes métodos de simulação para modelar diferentes aspetos que influenciam um processo. A simulação baseada em agentes (ABS) e BPMN são escolhidas como os dois métodos de simulação para estudar o potencial dessa integração em processos de negócio, e a nossa abordagem para os combinar consiste em modelar o comportamento do utilizador em ABS e o próprio processo de negócio utilizando o BPMN. Por fim, a integração entre os dois motores de simulação acontece durante o decurso da simulação através da invocação de APIs usando o protocolo REST, onde os agentes controlam a dinâmica de execução do processo no BPMN. Esta abordagem de integração é validada através da construção de uma experiência, com o objetivo de determinar se os resultados de simulação obtidos são estatisticamente coerentesThe current paradigm of a business process model is that it is a representation of a sequence of tasks that act upon some data input, to produce an output, aiming the production of a new service or product to be delivered from a producer to a customer. Although this is a valid way of thinking, it neglects to consider in enough detail the influence of some phenomenon on inputs, e.g. human behaviour, communication, social interactions, the organisational culture which can have a significant effect on the output delivered by a business process. As the dynamics of these phenomena are non-linear, they can be interpreted as a complex system. This holistic way of thinking about business processes opens the doors to the possibility of combining different simulation methods to model different aspects that influence a process. A BPMN engine and an agent-based simulation (ABS) engine are chosen to serve the basis of our framework. In its conception, we not only consider the technical aspects of the framework but also delve into exploring its management and organizational dimensions, with the intent of facilitating its adoption in enterprises, as a tool to support decision support systems. We analyse how accurate the simulation results can be when using these two tools as well as what considerations need to be considered within organizations

Process control and configuration of a reconfigurable production system using a multi-agent software system

Thesis (M. Tech. (Information Technology)) -- Central University of technology, Free State, 2011Traditional designs for component-handling platforms are rigidly linked to the product being produced. Control and monitoring methods for these platforms consist of various proprietary hardware controllers containing the control logic for the production process. Should the configuration of the component handling platform change, the controllers need to be taken offline and reprogrammed to take the changes into account. The current thinking in component-handling system design is the notion of re-configurability. Reconfigurability means that with minimum or no downtime the system can be adapted to produce another product type or overcome a device failure. The re-configurable component handling platform is built-up from groups of independent devices. These groups or cells are each responsible for some aspect of the overall production process. By moving or swopping different versions of these cells within the component-handling platform, re-configurability is achieved. Such a dynamic system requires a flexible communications platform and high-level software control architecture to accommodate the reconfigurable nature of the system. This work represents the design and testing of the core of a re-configurable production control software platform. Multiple software components work together to control and monitor a re-configurable component handling platform. The design and implementation of a production database, production ontology, communications architecture and the core multi-agent control application linking all these components together is presented

Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives

Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future

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

[ES]Hasta el momento no se conocen modelos de tiempo real específicamente 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 integración de agentes en tiempo real dentro de OVs. Hasta donde alcanza nuestro conocimiento, éste es el primer modelo específicamente diseñado para su aplicación 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. Ésto es una aspecto complicado ya que el primer paradigma no es estricto, como el propio término 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 ejecución de un plan particular. Es una planificación de tiempo real en una OV. Otra de las principales contribuciones de esta tesis es un modelo para el cálculo del tiempo de ejecución 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 ejecución. También se incluye una planificación local para cada nodo de ejecución basada en el algoritmo FPS y una distribución de tareas entre los nodos disponibles en el sistema. Para ambos modelos se usan modelos matemáticos y estadísticos 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 gestión de OVs, es la principal motivación para el desarrollo de la plataforma de agentes PANGEA+RT. PANGEA+RT es una innovadora plataforma multi-agente que proporciona soporte para la ejecución de agentes en ambientes de tiempo real. Finalmente, se presenta un caso de estudio donde robots heterogéneos colaboran para realizar tareas de vigilancia. El caso de estudio se ha desarrollado con la plataforma PANGEA+RT donde el modelo propuesto está integrado. Por tanto al final de la tesis, con este caso de estudio se obtienen los resultados y conclusiones que validan el modelo

Real-time guarantees in high-level agent programming languages

In the thesis we present a new approach to providing soft real-time guarantees for Belief-Desire-Intention (BDI) agents. We analyse real-time guarantees for BDI agents and show how these can be achieved within a generic BDI programming framework. As an illustration of our approach, we develop a new agent architecture, called AgentSpeak(RT), and its associated programming language, which allows the development of real-time BDI agents. AgentSpeak(RT) extends AgentSpeak(L) [28] intentions with deadlines which specify the time by which the agent should respond to an event, and priorities which specify the relative importance of responding to a particular event. The AgentSpeak(RT) interpreter commits to a priority-maximal set of intentions: a set of intentions that is maximally feasible while preferring higher priority intentions. Real-time tasks can be freely mixed with tasks for which no deadline and/or priority has been specified, and if no deadlines and priorities are specified, the behavior of the agent defaults to that of a non real-time BDI agent. We perform a detailed case study of the use of AgentSpeak(RT) to demonstrate its advantages. This case study involves the development of an intelligent control system for a simple model of a nuclear power plant. We also prove some properties of the AgentSpeak(RT) architecture such as guaranteed reactivity delay of the AgentSpeak(RT) interpreter and probabilistic guarantees of successful execution of intentions by their deadlines. We extend the AgentSpeak(RT) architecture to allow the parallel execution of intentions. We present a multitasking approach to the parallel execution of intentions in the AgentSpeak(RT) architecture. We demonstrate advantages of parallel execution of intentions in AgentSpeak(RT) by showing how it improves behaviour of the intelligent control system for the nuclear power plant. We prove real-time guarantees of the extended AgentSpeak(RT) architecture. We present a characterisation of real-time task environments for an agent, and describe how it relates to AgentSpeak(RT) execution time profiles for a plan and an action. We also show a relationship between the estimated execution time of a plan in a particular environment and the syntactic complexity of an agent program

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF