Catálogo de publicaciones - libros

In this paper we explore the concept of a Semantic Desktop in which software applications will be responsible for the automation of otherwise tedious tasks and the update of user information. We propose an ontology driven software agent solution where two major issues stand out: architecture and process. The architecture issue addresses the current static nature of information on a web page. In order to achieve the level of pro-activity desired we have to be able to identify, classify and code important bits of semantic information in a way that can be automatically manipulated by machines. The second issue relates to the strategy/strategies used to dynamically update information. Because of the variety of actions needed to update web sites e.g., monitoring changes to personal information (phone numbers, addresses, hobbies, etc.), maintaining a knowledge of institutional information, reacting to external events, reaction to political and environmental changes, etc., we hypothesize that no single strategy for maintaining dynamic information-awareness will do but that a variety of strategies need to be put into practice. We propose the creation of a community of software agents, each responsible for achieving a different set of tasks. The Semantic Desktop is achieved through the composition of the site semantics with the functionality provided by the instantiated software agents.

We investigate a formal framework where agents use referrals from other agents to locate high-quality service providers. Agents have common knowledge about providers which are able to provide these services. The performance of providers is measured by the satisfaction obtained by agents from using their services. Provider performance varies with their current load. We assume that agents are truthful in reporting interaction experiences with providers and refer the highest quality provider known for a given task. The referral mechanism is based of the exchange value theory. Agents exchange both the name of the provider to use and the satisfaction obtained by using a referred provider. We present an algorithm for selecting a service provider for a given task which includes mechanisms for deciding when and who to ask for a referral. This mechanism requires learning, over interactions, both the performance levels of different service providers, as well as the quality of referrals provided by other agents. We use a satisficing rather than an optimizing framework, where agents are content to receive service quality above a threshold. We experimentally demonstrate the effectiveness of our algorithm in producing stable system configurations where reasonable satisfaction expectations of all agents are met.

Industrial need new technologies to make evolved methods, strategy and capacity. Decision-making plays an important role in the case of the robot evolving in an instable environment, and enables us to decreasing the human factor in the control system. This paper presents a model based on brain construction to give a restricted emotion to a machine in order to control a multitude of entities. Emotion permits to make a rapid decision in a hostile environment. The method used to build this system is based on Massive MultiAgent System (Massive MAS). It enables us to have a vast number of entities with an asynchronous communication.The morphologic aspect is used to observe the agents behavior with the aim to generate a restricted emotion in order to make an action plan.

We tackle the notion of self-adaptive systems in an organizational way as complex systems with strong motivated autonomous behavior leading to the emotions. The main applications of such systems are in autonomous robots. We show that we need a new approach to build such systems where we use an adaptive construction grounded on software organizations of agents, using inner loops like the feedback loops of electronic, but in the agent world. The management of the activations loops by the system itself, using the notion of shape of the loops, expresses the concept computable concept of emotion.

In this paper, we present a new and novel way of maintaining the consistency in an agent’s knowledge base relying on the notion of Truth Maintenance Systems. In our work, we present a new parameter that helps in determining which propositions or assertions to retract if a contradiction ensues. Our new soundness parameter will be very easy to compute, at the same time, it is very effective.

This article advocates the need for a radical rethink of software agent technology by investigating the mechanisms through which knowledge, deliberation, action and control interact to form truly intelligent autonomous agents, be they deliberative, intentional or purely reactive automata/ particles/actors. Using sound logical formal modelling techniques, this work attempts to propose a unified model of multi-agency, which integrates and consolidates various proposed software agent models including; deliberative, cognitive, collectivist and individualist agent perspectives. In particular, the paper focuses on the formal semantics of model-based and emergent regulatory structure of autonomic self-regenerative systems, agents or particles (swarm intelligence). In addition, the paper uses our new scripting language – Neptune and associated development environment, which transforms formal require-ments models of a given agency to executable code.

A multiagent architecture for vehicle and structural health monitoring is proposed. A prototype using this architecture was developed using JADE. Critical aspects of the design were verified using the SPIN model checker. The tasks in our framework are related to data-fusion levels and Gibson’s realist position on direct perception of objects and affordances. We show how a system consisting of a multiagent system along with the monitored platform exhibits behavior at several levels, from the physics of acoustic emissions to inter-agent conversations expressing desires and beliefs. Communication, perception of public events, and system design conspire to provide the common knowledge needed to coordinate diagnostic tasks.

Model-driven development generates software artifacts from abstract model representations through a series of specification elaboration and refinement activities. Yet, the resulting systems must still be debugged at the source code level; leaving it to the developer to associate the symptoms found during debugging with the root causes in the models. Abstractions in the model result in difficulties correlating between models (where changes are made) and the artifacts (where effects of the changes occur). This paper examines the issues involved in debugging systems produced using a model-driven approach and proposes an architecture for a model level debugger based on our work on the Cougaar Model Driven Architecture (CMDA). We present an approach that mimics current debuggers by storing the relevant mapping and transform information in the model repository during generation and then using it to construct the debugging structures needed for examining the program during execution from the model perspective.

On the one hand, the Software Product Lines (SPL) field is devoted to build a core architecture for a family of products from which concrete products can be derived rapidly by means of reuse. On the other hand, Agent-Oriented Software Engineering (AOSE) is a software engineering paradigms dedicated to build software applications composed of organizations of agents. Bringing AOSE to the industrial world may prettily benefit from SPL advantages. Using SPL philosophy, a company will be able to define a core MAS from which concrete products will be derived for each customer. This can reduce time-to-market, costs, etcetera. In this paper, we expose the similarities between AOSE and SPL concluding the viability of future research in Multi-Agent Systems Product Lines (MAS-PL).

In this paper, which is exploratory in nature, we introduce the concept of , which from our point of view arise from the convergence of two research areas: electronic institutions and coalition formation. We define dynamic electronic institutions as emergent associations (coalitions) of intelligent, autonomous and heterogeneous agents, which play different roles, and which are able to adopt a set of norms in order to interact with each other, with the aim of satisfying individual goals and/or common goals. These formations are dynamic in the sense that they can be automatically formed, reformed and dissolved, in order to constitute temporary electronic institutions on the fly. This type of institution should be able to adapt its norms and objectives dynamically in relation to its present members (agents). In this paper we introduce some preliminary ideas on how these systems could be developed, and present our first exploratory work. We argue that dynamic electronic institutions are potentially important in open-agent system applications.