Today in the Serious Games market there is a need to develop a new educational program for crew members of Navy vessels. These kinds of Serious Games have the potential to be reused and provided to the navies of other nations. For instance, in the RAMSES project, several scenarios involving Intelligent Agents and virtual distributed simulation are currently being developed by the authors to meet custom needs in the context of a marine environment. These include scenarios for Autonomous Underwater Vehicle (AUV) operations and Special Forces’ surveillance and protection of ships and other marine infrastructure. Two prototypes have been produced and others are being developed.

Some of the innovations of this research include the possibility, through IA, to simplify the preparation and execution of training sessions, which in our research has corresponded to a reduction of training costs and time. Therefore one re-engineers the educational process using technological solutions that are able to generate, execute, and evaluate the training session in an easy way according to users’ needs.

The RAMSES-SG team developed the Games included in RAMSES-SG project by testing different tools, in particular: VBS2 and VBS World, Unity, VEGA, Delta and Thinking Worlds. Intelligent Agents are being implemented by SG-IA in order to allow for a Serious Games (SG) evolution and platform devoted to training scenario execution, the GUIs (Graphic User Interfaces) for trainee (SG-TE) and Instructor (SG-TR) architecture. SG allows for the generation of the scenario. The training scenario is executed and initialized by SG, and trainees learn to manage difficult operations, while cooperating within the game with other players, thanks to a user interface (i.e. virtual simulation) that is made possible by SG-TE. Implementation of several kinds of actions and decisions that are influenced by cooperation with other players within the game are made possible through SG-IA. Serious Games-IA allow for different scenario development according to what happens in reality where events are the consequences of crew members’ decisions. Currently the authors are developing a module devoted to providing the simulator with a system through which trainers are able to evaluate trainee performance based on data provided by SG-AR. The Serious Games allows for cooperative training when a user trains alone thanks to the presence of Intelligent Agents and distributed simulation architectures. It is possible to train crew members outside specific training structures with a federation of different simulators cooperating among trainees and instructors who might live in different countries. Learning process requirements are ensured by the integration of SG-TR, SG-TE, and SG operation/physics and behavior fidelity level which are made possible by the collection of required data. The result is an advanced framework that allows trainees to pursue effective learning results through an understanding of the importance of cooperation with other players (virtual and real ones) and the organization of information. The game provides the players with a set of possible actions that they have to carry out cooperating with others.

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