19,418 research outputs found
Model Driven Evolution of an Agent-Based Home Energy Management System
Advanced smart home appliances and new models of energy tariffs imposed
by energy providers pose new challenges in the automation of home energy
management. Users need some assistant tool that helps them to make complex decisions
with different goals, depending on the current situation. Multi-agent systems
have proved to be a suitable technology to develop self-management systems,
able to take the most adequate decision under different context-dependent situations,
like the home energy management. The heterogeneity of home appliances
and also the changes in the energy policies of providers introduce the necessity of
explicitly modeling this variability. But, multi-agent systems lack of mechanisms
to effectively deal with the different degrees of variability required by these kinds
of systems. Software Product Line technologies, including variability models, has
been successfully applied to different domains to explicitly model any kind of variability.
We have defined a software product line development process that performs
a model driven generation of agents embedded in heterogeneous smart objects with
different degrees of self-management. However, once deployed, the home energy
assistant system has to be able to evolve to self-adapt its decision making or devices
to new requirements. So, in this paper we propose a model driven mechanism to
automatically manage the evolution of multi-agent systems distributed among several
devices.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
Fighting Poverty, Profitably: Transforming the Economics of Payments to Build Sustainable, Inclusive Financial Systems
The Gates Foundation's Financial Services for the Poor program (FSP) believes that effective financial services are paramount in the fight against poverty. Nonetheless, today more than 2 billion people live outside the formal financial sector. Increasing their access to high quality, affordable financial services will accelerate the well-being of households, communities, and economies in the developing world. One of the most promising ways to deliver these financial services to the poor -- profitably and at scale -- is by using digital payment platforms.These are the conclusions we have reached as the result of extensive research in pursuit of one of the Foundation's primary missions: to give the world's poorest people the chance to lift themselves out of hunger and extreme poverty.FSP conducted this research because we believe that there is a gap in the fact base and understanding of how payment systems can extend digital services to low income consumers in developing markets. This is a complex topic, with fragmented information and a high degree of country-by-country variability. A complete view across the entire payment system has been missing, limiting how system providers, policy makers, and regulators (groups we refer to collectively as financial inclusion stakeholders) evaluate decisions and take actions. With a holistic view of the payment system, we believe that interventions can have higher impact, and stakeholders can better understand and address the ripple effects that changes to one part of the system can have. In this report, we focus on the economics of payment systems to understand how they can be transformed to serve poor people in a way that is profitable and sustainable in aggregate
Moving from Data-Constrained to Data-Enabled Research: Experiences and Challenges in Collecting, Validating and Analyzing Large-Scale e-Commerce Data
Widespread e-commerce activity on the Internet has led to new opportunities
to collect vast amounts of micro-level market and nonmarket data. In this paper
we share our experiences in collecting, validating, storing and analyzing large
Internet-based data sets in the area of online auctions, music file sharing and
online retailer pricing. We demonstrate how such data can advance knowledge by
facilitating sharper and more extensive tests of existing theories and by
offering observational underpinnings for the development of new theories. Just
as experimental economics pushed the frontiers of economic thought by enabling
the testing of numerous theories of economic behavior in the environment of a
controlled laboratory, we believe that observing, often over extended periods
of time, real-world agents participating in market and nonmarket activity on
the Internet can lead us to develop and test a variety of new theories.
Internet data gathering is not controlled experimentation. We cannot randomly
assign participants to treatments or determine event orderings. Internet data
gathering does offer potentially large data sets with repeated observation of
individual choices and action. In addition, the automated data collection holds
promise for greatly reduced cost per observation. Our methods rely on
technological advances in automated data collection agents. Significant
challenges remain in developing appropriate sampling techniques integrating
data from heterogeneous sources in a variety of formats, constructing
generalizable processes and understanding legal constraints. Despite these
challenges, the early evidence from those who have harvested and analyzed large
amounts of e-commerce data points toward a significant leap in our ability to
understand the functioning of electronic commerce.Comment: Published at http://dx.doi.org/10.1214/088342306000000231 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Deep Space Network information system architecture study
The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control
Practical applications of multi-agent systems in electric power systems
The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur
Early aspects: aspect-oriented requirements engineering and architecture design
This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications
An assembly oriented design framework for product structure engineering and assembly sequence planning
The paper describes a novel framework for an assembly-oriented design (AOD) approach as a new functional product lifecycle management (PLM) strategy, by considering product design and assembly sequence planning phases concurrently. Integration issues of product life cycle into the product development process have received much attention over the last two decades, especially at the detailed design stage. The main objective of the research is to define assembly sequence into preliminary design stages by introducing and applying assembly process knowledge in order to provide an assembly context knowledge to support life-oriented product development process, particularly for product structuring. The proposed framework highlights a novel algorithm based on a mathematical model integrating boundary conditions related to DFA rules, engineering decisions for assembly sequence and the product structure definition. This framework has been implemented in a new system called PEGASUS considered as an AOD module for a PLM system. A case study of applying the framework to a catalytic-converter and diesel particulate filter sub-system, belonging to an exhaust system from an industrial automotive supplier, is introduced to illustrate the efficiency of the proposed AOD methodology
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