Manufacture and Test of a Small Ceramic-Insulated Nb3_{3}Sn Split Solenoid

A small split solenoid wound with high-Jc Nb$_{3}$Sn conductor, constituted by a 0.8 mm Rod Re-stack Process (RRP®) strand, was built and tested at CERN in order to study the applicability of: 1) ceramic wet glass braid insulation without epoxy impregnation of the magnet; 2) a new heat treatment devised at CERN and particularly suitable for reacting RRP® Nb$_{3}$Sn strands. This paper briefly describes the solenoid and the experimental results obtained during 4.4 K and 1.9 K tests. The split solenoid consists of two coils (25 mm inner diameter, 51.1 mm outer diameter, 12.9 mm height). The coils were initially separately tested, in an iron mirror configuration, and then tested together in split solenoid configuration. In all the tests at 4.4 K the coils reached a current higher than 95 % of their short sample limits at the first quench; in split solenoid configuration the maximum field values in the coils and in the aperture were respectively 10.7 T and 12.5 T. At 1.9 K the coils had premature quenches due to self field instability despite the rather high RRR of the two coils (190 and 270). This phenomenon at 1.9 K, predicted by our theory [1], was confirmed by strand measurements

A multi-agent system to manage users and spaces in a adaptive environment system

This paper, deals with the actual problem of manage user preferences and local specifications on an IoT adaptive system, namely using a multi agent system to achieve a Smart Environment System. On a new era of interaction between persons and physical spaces, users want those spaces smartly adapt to their preferences in a transparent way. To achieve that, new approaches are needed. In this project we develop a multi agent system architecture with different layers to achieve a solution that entails all the proposed objectives.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019

Meta-Information and Argumentation in Multi-Agent Systems

In this work we compile our research regarding meta-information in multi-agent systems. In particular, we describe some agents profiles represent- ing different attitudes which describe how agents consider meta-information in their decisions-making and reasoning processes. Furthermore, we describe how we have combined different meta-information available in multi-agent systems with an argumentation-based reasoning mechanism. In our approach, agents are able to decide more conflicts between information/arguments, given that they are able to use different meta-information (often combined) to decide between such conflicting information. Our framework for meta-information in multi- agent systems was implemented based on a modular architecture, thus other meta-information can be added, as well as different meta-information can be combined in order to create new agents profiles. Therefore, in our approach, different agents profiles can be instantiated for different application domains, allowing flexibility in the choice of how agents will deal with conflicting infor- mation in those particular domains

Using jason framework to develop a multi-agent system to manage users and spaces in an adaptive environment system

Manage user preferences and local specifications on an IoT adaptive system is a actual problem. This paper uses Jason framework to develop a multi agent system to achieve a Smart Environment System, and supports interaction between persons and physical spaces, that users want to smartly adapt to their preferences in a transparent way. This work proposes a new approach, that has been developed using a multi agent system architecture with different layers to achieve a solution that entails all the proposed objectives.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019

RV4JaCa - Runtime Verification for Multi-Agent Systems

This paper presents a Runtime Verification (RV) approach for Multi-Agent Systems (MAS) using the JaCaMo framework. Our objective is to bring a layer of security to the MAS. This layer is capable of controlling events during the execution of the system without needing a specific implementation in the behaviour of each agent to recognise the events. MAS have been used in the context of hybrid intelligence. This use requires communication between software agents and human beings. In some cases, communication takes place via natural language dialogues. However, this kind of communication brings us to a concern related to controlling the flow of dialogue so that agents can prevent any change in the topic of discussion that could impair their reasoning. We demonstrate the implementation of a monitor that aims to control this dialogue flow in a MAS that communicates with the user through natural language to aid decision-making in hospital bed allocation

Explaining Semantic Reasoning Using Argumentation

Multi-Agent Systems (MAS) are popular because they provide a paradigm that naturally meets the current demand to design and implement distributed intelligent systems. When developing a multi-agent application, it is common to use ontologies to provide the domain-specific knowledge and vocabulary necessary for agents to achieve the system goals. In this paper, we propose an approach in which agents can query semantic reasoners and use the received inferences to build explanations for such reasoning. Also, thanks to an internal representation of inference rules used to build explanations, in the form of argumentation schemes, agents are able to reason and make decisions based on the answers from the semantic reasoner. Furthermore, agents can communicate the built explanation to other agents and humans, using computational or natural language representations of arguments. Our approach paves the way towards multi-agent systems able to provide explanations from the reasoning carried out by semantic reasoners

Incorporating social practices in BDI agent systems

When agents interact with humans, either through embodied agents or because they are embedded in a robot, it would be easy if they could use fixed interaction protocols as they do with other agents. However, people do not keep fixed protocols in their day-to-day interactions and the environments are often dynamic, making it impossible to use fixed protocols. Deliberating about interactions from fundamentals is not very scalable either, because in that case all possible reactions of a user have to be considered in the plans. In this paper we argue that social practices can be used as an inspiration for designing flexible and scalable interaction mechanisms that are also robust. However, using social practices requires extending the traditional BDI deliberation cycle to monitor landmark states and perform expected actions by leveraging existing plans. We define and implement this mechanism in Jason using a periodically run meta-deliberation plan, supported by a metainterpreter, and illustrate its use in a realistic scenario.Comment: An extended abstract of this paper has been accepted for the Eighteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 201

A survey on parallel and distributed Multi-Agent Systems

International audienceSimulation has become an indispensable tool for researchers to explore systems without having recourse to real experiments. Depending on the characteristics of the modeled system, methods used to represent the system may vary. Multi-agent systems are, thus, often used to model and simulate complex systems. Whatever modeling type used, increasing the size and the precision of the model increases the amount of computation, requiring the use of parallel systems when it becomes too large. In this paper, we focus on parallel platforms that support multi-agent simulations. Our contribution is a survey on existing platforms and their evaluation in the context of high performance computing. We present a qualitative analysis, mainly based on platform properties, then a performance comparison using the same agent model implemented on each platform