Infrastructure for Detector Research and Development towards the International Linear Collider

The EUDET-project was launched to create an infrastructure for developing and testing new and advanced detector technologies to be used at a future linear collider. The aim was to make possible experimentation and analysis of data for institutes, which otherwise could not be realized due to lack of resources. The infrastructure comprised an analysis and software network, and instrumentation infrastructures for tracking detectors as well as for calorimetry.Comment: 54 pages, 48 picture

7th Drug hypersensitivity meeting: part two

No abstract availabl

A Multi-Agent System Performing One-to-Many Negotiation for Load Balancing of Electricity Use

Emerging technologies allowing two-way communication between utility companies and their customers are changing the rules of the energy market. Deregulation makes it even more demanding for utility companies to create new business processes for the mutual benefit of the companies and their customers. Dynamic load management of the power grid is essential to make better and more cost-effective use of electricity production capabilities, and to increase customer satisfaction. In this paper, methods from agent technology and knowledge technology have been used to analyse, design, and implement a component-based multi-agent system capable of negotiation for load management. The proof-of-concept prototype system NALM (negotiating agents for load management) developed shows how under certain assumptions peaks in power load can be reduced effectively based on a negotiation process. © Elsevier Science B.V. All rights reserved

Compositional Design and Verification of a Multi-Agent System for One-to-Many Negotiation

Contains fulltext : 63995.pdf (publisher's version ) (Open Access)Verification of multi-agent systems hardly occurs in design practice. One of the difficulties is that required properties for a multi-agent system usually refer to multi-agent behaviour which has nontrivial dynamics. To constrain these multi-agent behavioural dynamics, often a form of organisational structure is used, for example, for negotiating agents, by following strict protocols. The claim is that these negotiation protocols entail a structured process that is manageable with respect to analysis, design and execution of such a multi-agent system. In this paper this is shown by a case study: verification of a multi-agent system for one-to-many negotiation in the domain of load balancing of electricity use. A compositional verification method for multi-agent systems is applied that allows to (1) logically relate dynamic properties of the multi-agent system as a whole to dynamic properties of agents, and (2) logically relate dynamic properties of agents to properties of their subcomponents. Given that properties of these subcomponents can be verified by more standard methods, these logical relationships provide proofs of the dynamic properties of the multi-agent system as a whole

Compositional Design and Verification of a Multi-Agent System for One-to-Many Negotiation

Contains fulltext : 63995.pdf (publisher's version ) (Open Access)Verification of multi-agent systems hardly occurs in design practice. One of the difficulties is that required properties for a multi-agent system usually refer to multi-agent behaviour which has nontrivial dynamics. To constrain these multi-agent behavioural dynamics, often a form of organisational structure is used, for example, for negotiating agents, by following strict protocols. The claim is that these negotiation protocols entail a structured process that is manageable with respect to analysis, design and execution of such a multi-agent system. In this paper this is shown by a case study: verification of a multi-agent system for one-to-many negotiation in the domain of load balancing of electricity use. A compositional verification method for multi-agent systems is applied that allows to (1) logically relate dynamic properties of the multi-agent system as a whole to dynamic properties of agents, and (2) logically relate dynamic properties of agents to properties of their subcomponents. Given that properties of these subcomponents can be verified by more standard methods, these logical relationships provide proofs of the dynamic properties of the multi-agent system as a whole