Jorge J. Gómez-Sanz

Agent oriented software engineering with INGENIAS

INGENIAS is both a methodology and a set of tools for development of multi-agent systems (MAS). As a methodology, it tries to integrate results from other proposals and considers the MAS from five complementary viewpoints: organization, agent, tasks/goals, interactions, and environment. It is supported by a set of tools for modelling (graphical editor), documentation and code generation (for different agent platforms). INGENIAS is the result of the experience developing MAS in different areas, such as workflow management systems, recommender systems, Robocode teams, and PC assistants

FAML: A Generic Metamodel for MAS Development

In some areas of software engineering research, there are several metamodels claiming to capture the main issues. Though it is profitable to have variety at the beginning of a research field, after some time, the diversity of metamodels becomes an obstacle, for instance to the sharing of results between research groups. To reach consensus and unification of existing metamodels, metamodel-driven software language engineering can be applied. This paper illustrates an application of software language engineering in the agent-oriented software engineering research domain. Here, we introduce a relatively generic agent-oriented metamodel whose suitability for supporting modeling language development is demonstrated by evaluating it with respect to several existing methodology-specific metamodels. First, the metamodel is constructed by a combination of bottom-up and top-down analysis and best practice. The concepts thus obtained and their relationships are then evaluated by mapping to two agent-oriented metamodels: TAO and Islander. We then refine the metamodel by extending the comparisons with the metamodels implicit or explicit within five more extant agent-oriented approaches: Adelfe, PASSI, Gaia, INGENIAS, and Tropos. The resultant FAML metamodel is a potential candidate for future standardization as an important component for engineering an agent modeling language.

Development of intelligent multisensor surveillance systems with agents

Intelligent multisensor surveillance systems consist of several types of sensors, which are installed on fixed and mobile devices. These components provide a huge quantity of information that has to be contrasted, correlated and integrated in order to recognize and react on special situations. These systems work in highly dynamic environments, with severe security and robustness requirements. All these characteristics imply the need for distributed solutions. In these solutions, scattered components can decide and act with some degree of autonomy (for instance, if they become isolated), or cooperate and coordinate for a complete tracking of special situations. In order to cope with these requirements and to better structure the solution, we have decided to design surveillance system control as a multiagent system. This is done by applying an agent-orientated methodology, which is assessed with concrete scenarios.

Model driven development of multi-agent systems

From a software engineering point of view, the agent paradigm has shown its potential for modelling in different domains. However, moving from agent models to implementation is not fully addressed by most agent-oriented methodologies in a systematic way. In most cases, they focus on the agent concept at the analysis level or look for visual or formal representations of elements present in an already implemented agent framework. Here we show that model driven development with agent-based models can facilitate the implementation of methods and tools for the development of multi-agent systems. This is illustrated with the INGENIAS methodology and its tools, the INGENIAS Development Kit (IDK), which are founded on the definition of the INGENIAS meta-models for multi-agent systems, and implement most of the facilities that a model driven development approach requires.

Understanding the human context in requirements elicitation

The human context within which a software system will operate is fundamental for its requirements. It may not appear to be very much related to the system, but it is very relevant in achieving its successful adoption. However, requirements engineers have usually a background in Software Engineering and are not trained to elicit this kind of information. This situation raises the need for analytical tools to deal with these features. These tools should enable collaborative work between requirements engineers, who use them in development, social practitioners, who provide the knowledge and processes underlying these tools, and the customers, who know the domain and intended application of the projects. The framework presented in this paper is based on the socio-psychological Activity Theory and its analysis of human contexts. It includes a repository of social properties and a process to perform this elicitation using it. The paper illustrates its application through a case study on the impact of a new system in the organization of a firm.

Testing and Debugging of MAS Interactions with INGENIAS

Testing and debugging activities are getting more relevance in multi-agent systems (MAS) as agents become part of real applications. Both activities are related, since failures to be debugged are frequently detected during the execution of tests. The support for these activities is not yet as complete as other activities of MAS development. However, agent oriented software engineering methodologies are incorporating new testing and debugging features. In this direction, the paper introduces advances made in the INGENIAS agent development framework towards a complete coverage of testing and debugging activities. The advances are compared with respect to a categorisation of related works in the agent literature. This categorisation will be useful for evaluating and planning issues for improvement in the context of INGENIAS.

Modelling and simulation of social systems with INGENIAS

Most agent-based simulation toolkits are based on the Java programming language. This makes their use difficult for social scientists, who are usually not skilled in computer programming. However, agent modelling concepts are not unlike those which could be used for the modelling of social systems. This assumption is considered in proposing the use of a graphical agent-oriented language for the specification of social simulation models, and for transforming (automatically) these models to code for an agent-based simulation toolkit. In this manner, a social scientist could prepare social models in a more convenient way, and execute simulations on existing simulation toolkits, getting results back in terms of the model. This framework is built with a set of agent development tools, specifically, the INGENIAS Development Kit (IDK), which provides a customisable model editor and modules for automatic code generation.

Intelligent data analysis applied to debug complex software systems

The emergent behavior of complex systems, which arises from the interaction of multiple entities, can be difficult to validate, especially when the number of entities or their relationships grows. This validation requires understanding of what happens inside the system. In the case of multi-agent systems, which are complex systems as well, this understanding requires analyzing and interpreting execution traces containing agent specific information, deducing how the entities relate to each other, guessing which acquaintances are being built, and how the total amount of data can be interpreted. The paper introduces some techniques which have been applied in developments made with an agent oriented methodology, INGENIAS, which provides a framework for modeling complex agent oriented systems. These techniques can be regarded as intelligent data analysis techniques, all of which are oriented towards providing simplified representations of the system. These techniques range from raw data visualization to clustering and extraction of association rules.

Model driven development and simulations with the INGENIAS agent framework

Abstract The development of MAS can be facilitated with the introduction of simulations into the development process. The integration of simulations has been addressed by some agent oriented methodologies, generally defining mappings from the original Multi-Agent specification to concrete simulators like Repast or Sesame. This paper contributes with a deeper integration where the methodology becomes a generator of ad hoc simulators for the MAS under development. This is possible with the aid of Model Driven Engineering principles which derives executable Multi-Agent Systems automatically from a Multi-Agent System specification.

Activity Theory for the Analysis and Design of Multi-agent Systems

Modeling a Multi-Agent System (MAS) involves a large number of entities and relationships. This implies the need for defining an organization, in order to structure and manage the complexity of the whole system. In this work we propose the use of human organization metaphors and their application to the verification of MAS specification. In concrete, we apply Activity Theory, which has its roots in Sociology, to study agent systems and obtain relationship patterns that can be applied to the analysis of MAS. These patterns guide analysis and design refinements, and help to detect inconsistencies. This technique has been implemented and integrated in the INGENIAS IDE platform, and proved with some case studies, in particular, for agent-based web applications.