This paper proposes a formal model for specifying multi agent systems, named SyPN (for Synchronized Petri Net).  This model allows the specification of various kinds of agent-based systems’ behaviors, such as individual and collective behaviors. SyPN is an extension of Recursive Petri net allowing synchronization of several nets. In fact, SyPN borrows the specification of dynamic processes from Recursive Petri net and introduces several valuable concepts that enable concise multi agent system specifications, such as: typed places, transitions and tokens, synchronization points, synchronization condition, synchronization relation and binding function. We illustrate our approach by two case studies of remote interactions between agents.

For developing large dynamic systems in a rigorous manner, fuzzy labeled transition refinement tree (FLTRT for short) has been defined. This model provides a formal specification framework for designing such systems. In fact, it supports abstraction and enables fuzziness which allows a rigorous formal refinement process. The purpose of this paper is to illustrate the applicability of FLTRT for designing multi agent systems (MAS for short), among others collective and internal agent's behaviors. Therefore, Contract Net Protocol (CNP for short) is chosen as case study.

Nowadays, the Internet of things (IoT) is becoming a promising technology which revolutionizes and simplifies our daily life style. It allows interaction and cooperation between a large variety of pervasive objects over wireless and wired connections, in order to achieve specific goals. Moreover, it provides a concise integration of physical world into computer systems through network infrastructure. This paper provides an agent-based architecture for developing IoT systems. The proposed architecture is multi-layer and generic. It encompasses four layers: Physical Component Management, Local Management -Coordination, Global Management-Coordination and Specialized Operative Management Layers. The first one can be seen as a smart layer that ensures connection and communication between things and the system. The second one constitutes the intelligent core of the system which acts locally to ensure coordination and further internal functioning. The third layer ensures coordination between the local system and the externals ones. The last layer supports additional behaviors which are domain dependent. The architecture is illustrated by an IoT system diagnosis.

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Fuzzy Labeled Transition Refinement Tree (FLTRT) is a rigorous refinement model which supports abstraction and handling incomplete information and by the way reducing complexity of refinement process. It is based on Fuzzy Labeled Transition System (FLTS) which is a generalization of wellknown Labeled Transition System, enhanced by fuzziness facility. The FLTRT structure serves as a tree of potential concurrent design trajectories of the system. In this paper, we study bisimulation relations on FLTSs which are categorized into two classes: horizontal and vertical bisimulation relations. The former class aims to identify equivalent specifications of the same abstraction level. However, the second one relates specifications that belong conceptually to different abstraction levels. Vertical bisimulation relation aims to check correctness of a given implementation with respect to its initial specification. FLTRT structure preserves the vertical bisimulation relation.