Catálogo de publicaciones - libros

The deployment of multi-agent systems demands for justified confidence into their functioning, both with respect to correctness of behaviour and with respect to timeliness thereof. Depending on the stage of the development process different mechanisms and abstractions are needed to facilitate the evaluation of interacting agents. We propose a modelling and simulation framework based on a discrete-event formalism for supporting the development process of multi-agent systems; from specification to implementation. The framework allows for the incremental refinement of agents and experimental set-ups while providing rigorous observation facilities. The benefit of using discrete-event modelling and simulation techniques for evaluating agents is illustrated using a simple example based on the .

In this paper we present analysis and calibration techniques that exploit knowledge about a multi agent society in order to calibrate the system parameters of a corresponding society simulation model. The techniques address typical problems of multi agent simulation calibration like the vast amount of parameters that need to be calibrated, the complex parameter dependencies due to interactions between the simulated agents and the generally enormous computational cost of running a multi agent simulation.

We present an abstract declarative semantics for multi-agent systems based on the idea of , and argue that it can be suitably employed to describe, and to some extent verify, the dynamics of complex systems of autonomous and heterogeneous interacting agents. We view agents as black-boxes, whose semantics is abstractly understood as an input-output transformation from the agents’ observations about their environment, to the actions they perform. Stable sets (of actions) characterise multi-agent systems able to reach an equilibrium point. Our semantics via stable sets takes into account the possibility that agents may fail. We illustrate how stability can characterise multi-agent systems by means of examples. We also draw considerations about how stable sets can be effectively approximated.

Many problems studied in the multiagent systems community can be considered instances of an abstract multiagent resource allocation problem. In this problem, which is now better understood theoretically, the goal is to satisfy a criterion of global optimality (formulated in terms of a suitable notion of social welfare), given that the agents sharing a set of resources follow a local rationality criterion reflecting their individual preferences. In this paper, we first show that this simple decentralised resource allocation framework allows us to model a wide variety of applications. These applications thereby benefit from all the theoretical results concerning the framework. We then draw up a list of criteria which can guide the application designer working within the framework and illustrate the relevance of our approach by discussing several applications in view of this list of design criteria.