A Generalized Discrete Event System (G-DEVS) Flattened Simulation Structure: Application to High-Level Architecture (HLA) Compliant Simulation of Workflow

International audienceThe objective of the paper is to specify a new flattened Generalized Discrete Event System simulation engine structure and the Workflow modeling and simulation environment embedding it. We express first the new flattened simulation structure and give the corresponding transformation functions. We analyze performance tests conducted on this new simulation structure to measure its efficiency. Then, having selected the essential concepts in the elaboration of the Workflow, we present a language of description to define the Workflow processes. Finally, we define a distributed Workflow Reference Model that interfaces components of the Workflow with respect to the High-Level Architecture standard. Today enterprises can take advantage of this platform in the context of networking where interoperability, flexibility, and efficiency are challenging concepts

From Abstract Representation To Formal Modelling Of Tactical Military Operations

Situations where armed forces are now engaged have become more and more varied and complex far away from conventional confrontations. Hence, headquarters have an increasing need of a large variety of scenarios, quickly designed and implemented, in order to anticipate such new kind of situations. This is one of Piovra objectives to provide such kind of model of scenario. Recently, several efforts have arisen seeking similar goal but we choose to keep an high level model usable by end-users. This paper is to present how manage and connect these two levels of modelling: conceptual level for end-user and an operational level in order to perform simulations without platform constraints

Relocation of a flow-shop, without interrupting the production : optimization by DEVS modelisation and simulation

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G-DEVS/HLA Environment: A Time Management Improvement

Abstract- This paper presents a distributed discrete event simulation environment based on GDEVS and HLA concepts. The chosen local simulation structure is “flatten” to reduce the exchange of messages between simulation components regarding with classical structure of DEVS simulators. Moreover, we present an integration method to create GDEVS models HLA-compliant; for that purpose, we introduce an effective algorithm of conservative synchronization using the HLA lookahead and so improving the distributed simulation time management. Finally, we detail an example of distributed GDEVS coupled models to show the improvement due to the new algorithm

Improving Reinforcement Learning Of An Obstacle Avoidance Behavior With Forbidden Sequences Of Actions

This paper is concerned with the improvement of reinforcement learning through the use of forbidden sequences of actions. A given reinforcement function can generate multiple effective behaviors. Each behavior is effective only considering the cumulative reward over time. It may not be the behavior expected by the designer. In this case, the usual solution is to modified the reinforcement function so as to introduce a new constraint related to the behavioral aspect to express. Alternatively, we propose not to modify the reinforcement function, but to add an external module containing generic forbidden sequences of actions. Experiments with the real miniature robot Khepera in a task of learning an obstacle avoidance allow to confirm the interest of this approach. Key Words Reinforcement learning, obstacle avoidance, sequence, self-organizing map, autonomous robotics 1. Introduction This paper is concerned with the application of reinforcement learning to the control of a real robot tha..

Another way to manage supply chain

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Self Evaluation of Company’s Performance in partnership network

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Interoperability of Enterprises Network Holonic Control via HLA

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