Application of Model-driven engineering to multi-agent systems: a language to model behaviors of reactive agents

Many users of multi-agent systems (MAS) are very commonly disinclined to model and simulate using current MAS platforms. More specifically, modeling the dynamics of a system (in particular the agents' behaviors) is very often a challenge to MAS users. This issue is more often observed in the domain of socio-ecological systems (SES), because SES domain experts are rarely programmers. Indeed, the majority of MAS platforms were not conceived taking into consideration domain-experts who are non-programmers. Most current MAS tools are not dedicated to SES, or nor do they possess an easily understandable formalism to represent the behaviors of agents. Moreover, because it is platform-dependent, a model realized in a given MAS platform cannot be properly used on another platform due to incompatibility between MAS platforms. To overcome these limitations, we propose a domain-specific language (DSL) to describe the behaviors of reactive agents, regardless of the MAS platform used for simulation. To achieve this result, we used model-driven engineering (MDE), an approach that provides tools to develop DSLs from a meta-model (abstract syntax), textual editors with syntax highlighting (for the concrete syntax) and code generation capabilities (for source-code generation of a model). As a result, we implemented a language and a textual editor that allow SES domain experts to describe behaviors in three different ways that are close to their natural expression: as equations when they are familiar with these, as a sequence of activities close to natural language or as an activity diagram to represent decisions and a sequence of behaviors using a graphic formalism. To demonstrate interoperability, we also developed code generators targeting two different MAS platforms (Cormas and Netlogo). We tested the code generators by implementing two SES models with the developed DSL. The generated code was targeted to both MAS platforms (Cormas and Netlogo), and successfully simulated in one of them. We conclude that the MDE approach provides adequate tools to develop DSL and code generators to facilitate MAS modeling and simulation by non-programmers. Concerning the DSL developed, although the behavioral aspect of MAS simulation is part of the complexity of modeling in MAS, there are still other essential aspects of model and simulation of MAS that are yet to be explored, such as model initialization and points of view on the model simulated worl

Reusable and correct endogenous model transformations

Correctness of model transformations is a prerequisite for generating correct implementations from models. Given refining model transformations that preserve desirable properties, models can be transformed into correct-by-construction implementations. However, proving that model transformations preserve properties is far from trivial. Therefore, we aim for simple correctness proofs by designing model transformations that are as fine-grained as possible. Furthermore, we advocate the reuse of model transformations to reduce the number of proofs. For a simple domain-specific language, SLCO, we define a formal framework to reason about the correctness, reusability, and composition of the fine-grained model transformations used to transform a given model to three target languages: NQC, Promela and POOSL. The correctness criterion induces that the original model and the resulting model obtained after a proper sequence of transformations have the same observable behavior

Reusable and correct endogenous model transformations

Correctness of model transformations is a prerequisite for generating correct implementations from models. Given refining model transformations that preserve desirable properties, models can be transformed into correct-by-construction implementations. However, proving that model transformations preserve properties is far from trivial. Therefore, we aim for simple correctness proofs by designing model transformations that are as fine-grained as possible. Furthermore, we advocate the reuse of model transformations to reduce the number of proofs. For a simple domain-specific language, SLCO, we define a formal framework to reason about the correctness, reusability, and composition of the fine-grained model transformations used to transform a given model to three target languages: NQC, Promela and POOSL. The correctness criterion induces that the original model and the resulting model obtained after a proper sequence of transformations have the same observable behavior