Yann Secq

RIO: roles, interactions and organizations

The notions of role and organization have often been emphasized in several agent oriented methodologies. Sadly, the notion of interaction has seldom been reified in these methodologies. We define here a model of runnable specification of interaction protocols. Then, we propose a methodology for the design of open multi-agent systems based on an engineering of interaction protocols. These interaction protocols are described in term of conversation between micro-roles characterized by their skills, then micro-roles are gathered in composite roles. Then, composite roles are used to build abstract agents. Lastly, these latter can be distributed on running agents of a multi-agent system.

Effective Distribution of Large Scale Situated Agent-based Simulations

When we simulate a high number of agents and interactions in situated agent-based simulations, the necessary computing and storage needs to execute a time step can be increased dramatically. To be able to execute such simulations, it becomes mandatory to distribute the simulator over a computer network. More than the classical problematic in distributed systems, it is necessary to take into account specific aspects when we distribute a situated agents-based simulation, like agents and environment. This paper presents two types of distribution, one based on environment and the other on agents. We proof that some kinds of applications are more suitable for one distribution type than others. To proof this truth, experimentations have been done on two classical situated agent-based applications: flocking and prey-predator models.

Design patterns for environments in multi-agent simulations

In the field of multi-agent based simulation (MABS), the concept of environment is omnipresent, though poorly defined. We argue here that depending on the modeling of space and of relations between agents, only a few efficient implementations can be set up. We aim at formalizing the core functions of environments, so as to highlight the computational answers to possible modeling choices. This unifying approach leads to the identification of four paradigmatic Design Patterns, associated with specific atomic environments, which can be composed in order to tackle complex situations.

Towards a Pragmatic Methodology for Open Multi-agent Systems

This paper introduces the Rio methodology, which relies on the notions of Role, Interaction and Organization. We define a model of runnable specification of interaction protocols that represents interactions between agents globally, and that can be processed in orsder to generate Colored Petri Nets that handle agent conversations. Moreover, these specifications are not tied to a particular agent model and could therefore be used to enable multi-agent systems interoperability.

Towards a pragmatic use of ontologies in multi-agent platforms

The knowledge representation field is gaining momentum with the advent of the Semantic Web activity within the W3C. This working group, thanks to previous researches, has proposed the Ontology Web Language to enhance the expressivity of web pages and to allow semantic inferences. This paper argues that knowledge representation technologies should be core components of multi-agent platforms.

Using LCS to Exploit Order Book Data in Artificial Markets

In the study of financial phenomena, multi-agent market order-driven simulators are tools that can effectively test different economic assumptions. Many studies have focused on the analysis of adaptive learning agents carrying on prices. But the prices are a consequence of the matching orders. Reasoning about orders should help to anticipate future prices.

Synchronization Policies Impact in Distributed Agent-Based Simulation

When agents and interactions grow in a situated agent-based simulations, requirements in memory or computation power increase also. To be able to tackle simulation with millions of agents, distributing the simulator on a computer network is promising but raises issues related to time consistency and synchronization between machines. This paper study the cost in performances of several synchronization policies and their impact on macroscopic properties of simulations. To that aims, we study three different time management mechanisms and evaluate them on two multi-agent applications.

Simulating artifical stock markets with efficiency

Stock markets have been studied for years in economy and finance academic departments by relying on the idea of a general homo economicus that makes rational choices. Classical approaches use equational representation to enable a global markets characterization, but they fail to explain the link between individual behaviours and the global market dynamic and trends that emerge.