Interaction Biases in Multi-Agent Simulations: An Experimental Study

2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology

2008

Self Cite

To ensure multi-agent based simulation models reproducibility, particular attention must be payed on its possible implementation ambiguities. This concerns every aspect of simulation's architecture, including how the agent selects the actions it performs, and on which agents it is performed. On this point, classical agent-centered design methodologies leave room to implicit design choices.We show in this paper how an interaction-centered design methodology provides guidelines to elicit these choices, and to remove possible implementation ambiguities underlying agent design.To illustrate this issue, we study which ambiguities underly even simple models and how our interaction-based methodology makes them appear.

Section: Resultsmentioning

confidence: 97%

Section: Multi-agent Simulationsmentioning

confidence: 99%

Section: Multi-agent Simulationsmentioning

confidence: 99%

Section: Multi-agent Simulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Interaction Selection Ambiguities in Multi-agent Systems

2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology

2008

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How to Avoid Biases in Reactive Simulations

Advances in Intelligent and Soft Computing

2009

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In order to ensure simulations reproducibility, particular attention must be payed to the specification of its model. This requires adequate design methodologies, that enlightens modelers on possible implementation ambiguities -and biases 1 -their model might have. Yet, because of not adapted knowledge representation, current reactive simulation design methodologies lack specifications concerning interaction selection, especially in stochastic behaviors. Thanks to the interactionoriented methodology IODA -which knowledge representation is fit to handle such problems -this paper provides simple guidelines to describe interaction selection. These guidelines use a subsumption like-structure, and focus the design of interaction selection on two points : how the selection takes place -for instance first select the interaction, and then select the partner of the interaction, or first a partner and then an interaction -and the nature of each selection -for instance at random, or with a utility function. This provides a valuable communication support between modelers and computer scientists, that makes the interpretation of the model and its implementation clearer, and the identification of ambiguities and biases easier.

IODA: an interaction-oriented approach for multi-agent based simulations

Auton Agent Multi-Agent Syst

2011

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Multi-Agent Systems (MAS) design methodologies and Integrated DevelopmentEnvironments exhibit many interesting properties that also support simulation design. Yet, in their current form, they are not appropriate enough to model Multi-Agent Based Simulations (MABS). Indeed, their design is focused on the functionalities to be achieved by the MAS and the allocation of these functionalities among software agents. In that context, the most important point of design is the organization of the agents and how they communicate with each other. On the opposite, MABS aim at studying emergent phenomena, the origin of which lies in the interactions between entities and their interaction with the environment. In that context, the interactions are not limited to exchanging messages but can also be fundamental physical interactions or any other actions involving simultaneously the environment and one or several agents. To deal with this issue, this paper presents the core notions of the Interaction-Oriented Design of Agent simulations (IODA) approach to simulation design. It includes a design methodology, a model, an architecture and also JEDI, a simple implementation of IODA concepts for reactive agents. First of all, our approach focuses on the design of an agent-independent specification of behaviors, called interactions. These interactions are not limited to the analysis phase of simulation: they are made concrete both in the model and at the implementation stage. In addition, no distinction is made between agents and objects: all entities of the simulation are agents. Owing to this principle, designing which interactions occur between agents, as well as how agents act, is achieved by means of an intuitive plugand-play process, where interaction abilities are distributed among the agents. Besides, the guidelines provided by IODA are not limited to the specification of the model as they help the designer from the very beginning towards a concrete implementation of the simulation.