## 1 Introduction  
Today's production enterprises have to face a constantly changing market and fluctuating demand for customizable, high quality, and affordable products, in order to sustain their competitive advantage. The aforementioned factors are transformed into requirements imposed on the new-generation manufacturing systems [1, 2]. Such manufacturing systems should be able to cope with the dynamics of the entire system, with respect to its internal and external stimuli, uncertainties, and unexpected changes. They should, at the same time, be fault-tolerant, modular, and capable of dealing with disturbances as if they were a natural part of the system. Multi-agent systems (MASs) [3] are able to address these requirements and they offer additional features. These include autonomy, decentralization, scalability, and flexibility [4]. Inclusion of these features can be found in [3; 5]. Yet, MASs have not been widely adopted in the industrial domain. Several reasons for this were identified by [PERSON] and [PERSON] [6], particularly, the demand of the industry for mature technologies, initial investments, missing compliance with existing standards, the lack of development methodologies, insufficient interoperability, and integration with physical systems. There are also several areas in MASs--such as continuous, decentralized route planning for physical agents in a dynamic environment--that can still be challenging [7]. Several works were done in this field [8; 9]. This article uses delegates in the context of D-MASs (delegate multi-agent systems). Delegate or delegate agents are simple, reactive agents that are created, sent out, and collected by task and resource agents. Next, the features of delegate agents are that agents are virtual entities, not directly connected with anything physical, and that they communicate with other agents through the environment [8]. Primary agents or delegates use behavioral modules called D-MASs that reduce the agents' internal structural complexities; a definition can be found in [9]. The idea of our project was to create an intra-logistic system that can transport parts (i.e., manufacturing resources) and thus form a modular manufacturing line (MML). The resulting system is divided into two environments: virtual and real-world. The real-world part includes hardware prototypes and the environment-containing tools for their guidance. That part is reflected by the virtual part, which includes a virtual environment and agents. In order to obtain the properties required in such a system, we designed the following entities:  
* **MRS** (mobile robotic system): A bi-directional, real-world hardware prototype capable of transporting parts of an MML. It is bounded by the limited processing capacity and memory and it uses infrared optical sensors that allow it to be guided by a black tape [10]. * **MRSA** (mobile robotic system agent): A virtual entity mirroring its MRS. It provides transport services for modular platform agents. All decisions and interactions with other agents are made by the MRSA. The final decisions are encoded and sent to its MRS.
* **MP** (modular platform): A physical part of an MML that is able to connect to (or disconnect from) other modular platforms. It hosts a superstructure that can be a manufacturing or a logistic resource (robotic arm, conveyor, etc.). Superstructures and their agents are beyond the scope of this paper. * **MPA** (modular platform agent): Reflects an MP in the virtual environment. It uses the transport services of the MRSA (Figure 1). * **CA** (crossroad agent): Provides reservation services for an MRS's passage through its real-world counterpart. * **GG** (guidance grid): Composed of all crossroads (Figure 2). Note that the size of the crossroad is about the size of an MPA. This allows an MPA to connect to other MPAs when it is located at the center of a crossroad. Figure 1: The modular platform (MP) carried by the mobile robotic system (MRS) and their virtual counterparts. Figure 3 illustrates an artistic vision of our application.