Catálogo de publicaciones - libros

Software systems have become too complex to manage and fix manually. An emerging approach to overcome this problem is software self-healing. Studies in related disciplines have offered several self-healing solutions, however these usually address a single class of problems, or they are not applicable in fielded systems. To address the industrial need for software self-healing, we have initiated the EU SHADOWS project. This project concentrates on self-healing of complex systems, extending the state-of-art in several ways. It introduces pioneering technologies to enable the systematic self-healing of classes of failures which are not solved by other approaches. It additionally introduces an approach to the integration of several self-healing technologies in a common solution framework. It also adopts a model-based approach, where models of desired software behavior direct the self-healing process. Combined, these allow for lifecycle support of software self-healing, applicable to both academic and industrial systems.

The objective of the research described in this paper is to extend current agent platforms in order to provide both explicit, message-based and implicit, document-based communication and co-ordination within a uniform framework, and to make this unified framework available for the agent-oriented design and enactment of business processes. This is achieved by interfacing a BDI agent platform with an underlying peer-to-peer (P2P) platform, where the P2P framework is used to virtualize certain sections of the belief sets of the BDI agents; after a review of existing approaches to integrate multiagent with P2P concepts, a prototype technical realization is presented using two state-of-the art platforms: the Jack BDI agent platform and the P2P Business Resource Management Framework (BRMF) platform.

In the March 1942 issue of “Astounding Science Fiction”, Isaac Asimov for the first time enumerated his . Decades later, researchers in agents and multiagent systems have begun to examine these laws for providing a useful set of guarantees on deployed agent systems. Motivated by unexpected failures or behavior degradations in complex mixed agent-human teams, this paper for the first time focuses on applying Asimov’s first two laws to provide behavioral guarantees in such teams. However, operationalizing these laws in the context of such mixed agent-human teams raises three novel issues. First, while the laws were originally written for interaction of an individual robot and an individual human, clearly, our systems must operate in a team context. Second, key notions in these laws (e.g. causing “harm” to humans) are specified in very abstract terms and must be specified in concrete terms in implemented systems. Third, since removed from science-fiction, agents or humans may not have perfect information about the world, they must act based on these laws despite uncertainty of information. Addressing this uncertainty is a key thrust of this paper, and we illustrate that agents must detect and overcome such states of uncertainty while ensuring adherence to Asimov’s laws. We illustrate the results of two different domains that each have different approaches to operationalizing Asimov’s laws.

Application development on handheld devices using software agent technology is becoming more and more popular around the world. Escalation in the use of lightweight devices and PDA’s leads us to create a concrete base for future nomadic applications, positioned in a changing environment. However, constrained characteristics of handheld devices serve as the main hindrance towards achieving this goal. This paper presents the architecture of context aware FIPA complaint multi agent system for the lightweight devices called SAGE-Lite, which are capable of providing fault tolerance through the mechanism of object persistence. Agents existing on lightweight devices can communicate and provide services via Bluetooth and the communication with the server is done via WAP. Since agents communicate via sending and receiving ACL messages, this architecture will minimize communication latency with in the platform. This framework allows implementing agent-based applications like business applications or e-commerce applications on these resource-constrained devices.

This paper relates an experience in using a component model to design and construct agents. After discussing various rationales and architectural styles for decomposing an agent architecture, we describe a model of component for agents, named MALEVA. In this model, components encapsulate various units of agent behaviors (e.g., follow gradient, flee, reproduce). It provides an explicit notion of control flow between components (reified through specific control ports, connexions and components), for a fine grain control of activation and scheduling. Moreover, a notion of composite component allows complex behaviors to be constructed from simpler ones. Two examples, in the domain of multi-agent based simulation, are presented in this paper. They illustrate the ability of the model to facilitate both bottom-up and top-down approaches for agent design and construction and also to help at different types of potential reuse.

We report on a study in which twelve different paradigms were used to implement agents acting in an environment which borrows elements from artificial life and multi-player strategy games. In choosing the paradigms we strived to maintain a balance between high level, logic based approaches to low level, physics oriented models; between imperative programming, declarative approaches and “learning from basics” as well as between anthropomorphic or biologically inspired models on one hand and pragmatic, performance oriented approaches on the other.

Instead of strictly numerical comparisons (which can be applied to certain pairs of paradigms, but might be meaningless for others), we had chosen to view each paradigm as a methodology, and compare the design, development and debugging process of implementing the agents in the given paradigm.

We found that software engineering techniques could be easily applied to some approaches, while they appeared basically meaningless for other ones. The performance of some agents were easy to predict from the start of the development, for other ones, impossible. The effort required to achieve certain functionality varied widely between the different paradigms. Although far from providing a definitive verdict on the benefits of the different paradigms, our study provided a good insight into what type of conceptual, technical or organizational problems would a development team face depending on their choice of agent paradigm.

Belief-Desire-Intention (BDI) agents are well suited for autonomous applications in dynamic environments. Their precompiled plan schemata contain the procedural knowledge of an agent and contribute to the performance. The agents generally are constrained to a fixed set of action patterns. Their choice depends on current goals, not on the future of the environment. Planning techniques can provide dynamic plans regarding the predicted state of the environment. We augment a BDI framework with a state-based planner for operational planning in domains where BDI is not well applicable. For this purpose, the requirements for the planner and for the coupling with a BDI system are investigated. An approach is introduced where a BDI system takes responsibility for plan monitoring and re-planning and the planner for the creation of plans. A fast state-based planner utilizing domain specific control knowledge retains the responsiveness of the system. In order to facilitate integration with BDI systems programmed in object-oriented languages, the is adopted into the BDI conceptual space with object-based domain models. The application of the hybrid system is illustrated using a propositional puzzle and a multi agent coordination scenario.

This paper presents ALBA, a generic library dedicated to the commissioning of mobile agents written in Prolog. This library offers a handful of mechanisms for autonomous agent creation, execution, communication and mobility, whose implementation strongly respects the principles of robustness, decentralization of data, flexibility and genericity. In this perspective, the following paper mainly focuses on ALBA architecture and implementation with an emphasis on the technical choices which were made to provide these essential features. It therefore presents an innovative migration protocol, a research algorithm of agents solely identified by their names. It exposes some considerations about communication handling in a fully decentralized environment and some ideas towards a distributed modularity of systems. It also highlights an agent model, called Reasoning Threads, that is being used on top of ALBA to program cognitive agents.

This paper begins with the comparison of the message- sending mechanism, for communication among agents, and the method-invocation mechanism, for communication among objects. Then, we describe an extension of the method-invocation mechanism by introducing the notion of “sender” of a message, “state” of the interaction and “protocol” using the notion of “role”, as it has been introduced in the extension of Java. The use of roles in communication is shown by means of an example of protocol.

3APL is a widely known multi-agent programming language. However, when to be used in certain domains and environments, 3APL has some limitations related to its simplistic update operator that only allows for updates to the extensional part of the belief base and its lack of a language with both default and strong negation to enable the representation and reasoning about knowledge with the open and closed world assumptions. In this paper, we propose to address these issues by modifying the belief base of 3APL to be represented by Dynamic Logic Programming, an extension of Answer-Set Programming that allows for the representation of knowledge that changes with time.