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In the 21st century, enterprises face an increasingly competitive market place. In this context, the success of enterprises depends critically on the quality and efficiency of their product business processes. These processes generally aim to sell products or services. The approach presented in this paper aims at the assistance of teams following these processes. The underlying idea is to help team members in their daily tasks in order to be more efficient according to a specific process. The two main components of the approach are: an ontology for business processes modeling and aMulti-Agent System for providing intelligent assistance to the human workers. The Scrum software development process illustrates this approach. Scrum is an agile softwaredevelopment process widely used in software companies. This paper introduces a specific intelligent assistance software that aims to assist Scrum project teams in their implementation of the Scrum process. This tool aims primarily at helping Scrum Masters to take decisions by monitoring Scrum project teams' activities with their various projects and collecting knowledge about these activities. The proposed Scrum tool is a web-based system, which uses Multi-Agent System and the conceptualization of the Scrum process with a specific ontology. [ABSTRACT FROM AUTHOR]

This work focuses on the dynamic Pickup and Delivery Problem with Time Windows (PDPTW). The transport requests should be performed using the available fleet of vehicles. The vehicles move between the nodes of a road network. The aim of this work is to propose a model which allows, during a transport plan creation, to take into account predictable events. Particularly, we consider the frequency of requests at any node in the road network and the construction of vehicle routes that will allow new requests to be inserted without any significant route modification. Therefore, we construct routes that pass near the nodes where transport requests are most frequently generated.

A lot of work is devoted to formalizing and devising architectures for agents' cooperative behaviour, for coordinating the behaviour of individual agents within groups, as well as to designing agent societies using social laws. However, providing agents with abilities to automatically devise societies so as to form coherent emergent groups that coordinate their behaviour via social laws, is highly challenging. These systems are called self-organised. We are beginning to understand some of the ways in which self-organised agent systems can be devised. In this perspective, this paper provides several examples of multi-agent systems in which self-organisation, based on different mechanisms, is used to solve complex problems. Several criteria for comparison of self-organisation between the different applications are provided. [ABSTRACT FROM AUTHOR]

Nowadays, telemonitoring systems are increasingly used, due to the increasing of life expectancy and chronic diseases. Indeed, chronic diseases and disabilities due to advancing age are responsible for health care costs increasingly growing. Telemonitoring systems provide a low cost way to monitor patients and their needs in the comfort of their own homes. In first systems, the data were collected then sent directly to physicians to be interpreted. Nowadays, thanks to technological advancements, software and systems have been developed to process data, on a simple computer or even smartphone. In this paper, we present e-Care telemonitoring system that combines the semantic web and expert system. E-Care is based on generic ontologies and a decision support system. The decision support system uses ontologies as knowledge base and an inference engine to detect abnormal situations. E-Care platform has a generic open architecture, which cans include other knowledge coming from other systems. We'll show how to integrate data of auscultation sounds in this architecture. [ABSTRACT FROM AUTHOR]

Humans are able to estimate the depth of objects in their environment even using only one eye through the use of what are known as monocular cues. In this paper, we aim to integrate human knowledge and human-like reasoning used for monocular depth estimation within deep neural networks. The idea is to support the network in order to help it learn in an explicit and fast way the essential cues for the target task. For this purpose, we investigate the possibility of directly integrating geometric, semantic, and contextual information into the monocular depth estimation process. We propose exploiting an ontology model in a deep learning context to represent the urban environment as a structured set of concepts linked with semantic relationships. Monocular cues information are extracted through reasoning performed on the proposed ontology and are fed together with the RGB image in a multistream way into the deep neural network for depth estimation. Our approach is validated and evaluated on widespread benchmark datasets: KITTI, CityScapes, and AppolloScape. The obtained results show that the proposed method improves upon the state-of-the-art monocular depth estimation deep models and shows promising results regarding cross-evaluation, mainly for unseen driving scenarios. [ABSTRACT FROM AUTHOR]

Engineering projects are organizations where several actors with different professional fields and know-how work together to carry out the same aim: to develop a new product. Inside these organizations, heterogeneous and distributed information has to be managed in order to create project memories that will be useful in future projects. In this paper we describe a Multi-Agent System (MAS), which is based on the social and cooperative approach to support the knowledge management process all along mechanical design projects. Indeed, this multi-agent system, called KATRAS, aims to capitalize and reuse knowledge according to the roles involved in the design projects. We will present in this paper how the agents capitalize six different types of knowledge (professional vocabulary, process, expertise, project evolution, and return of experience) and how they help the professional actors to reuse knowledge. [ABSTRACT FROM AUTHOR]

The paper presents a critical review of the use of holonic paradigm in order to model and simulate traffic and transportation systems. After an introduction presenting the principles of this paradigm as well as its frameworks and concepts, the paper surveys existing works using the holonic paradigm for traffic and transportation applications. This is followed by a detailed analysis of the results of the survey. In particular, the relevance, the design approaches and the holonification orientation methodologies are investigated. Finally, based on this extensive review, open issues of holonic paradigm in modeling and simulation of traffic and transportation models are highlighted. [ABSTRACT FROM AUTHOR]