Agent-Based Demand-Modeling Framework for Large-Scale Microsimulations

Microsimulation is becoming increasingly important in traffic demand modeling. The major advantage over traditional four-step models is the ability to simulate each traveler individually. Decision-making processes can be included for each individual. Traffic demand is the result of the different decisions made by individuals; these decisions lead to plans that the individuals then try to optimize. Therefore, such microsimulation models need appropriate initial demand patterns for all given individuals. The challenge is to create individual demand patterns out of general input data. In practice, there is a large variety of input data, which can differ in quality, spatial resolution, purpose, and other characteristics. The challenge for a flexible demand-modeling framework is to combine the various data types to produce individual demand patterns. In addition, the modeling framework has to define precise interfaces to provide portability to other models, programs, and frameworks, and it should be suitable for large-scale applications that use many millions of individuals. Because the model has to be adaptable to the given input data, the framework needs to be easily extensible with new algorithms and models. The presented demand-modeling framework for large-scale scenarios fulfils all these requirements. By modeling the demand for two different scenarios (Zurich, Switzerland, and the German states of Berlin and Brandenburg), the framework shows its flexibility in aspects of diverse input data, interfaces to third-party products, spatial resolution, and last but not least, the modeling process itself

Plan's CCCD approach - Country study PLAN-Kenya

The field study for Kenya, a part of the strategic formative evaluation on CCCD, was carried out August 16-23, 2009. This country study aimed at studying CCCD as an approach for development and how it was applied by Plan Kenya. The executive summary covers the main findings and recommendations of the field study in Kenya. Detailed findings and recommendations concerning Plan Kenya are described in this report. Findings and recommendations when relevant are incorporated in the synthesis report: Strategic Evaluation Study on CCCD for Plan NLNO. After the introduction the report starts with an overview on the country context and Plan Kenya. The third chapter presents how Plan staff and partners view CCCD, fourth chapter is on how CCCD works in practice, chapter 5 looks in more detail on partnerships. The report ends with a summary of the findings and recommendations. CCCD was introduced in Kenya in 2004. Programmes undertaken by Plan Kenya do take child centredness and community development as their main point of departure

Collaborative hybrid agent provision of learner needs using ontology based semantic technology

© Springer International Publishing AG 2017. This paper describes the use of Intelligent Agents and Ontologies to implement knowledge navigation and learner choice when interacting with complex information locations. The paper is in two parts: the first looks at how Agent Based Semantic Technology can be used to give users a more personalised experience as an individual. The paper then looks to generalise this technology to allow users to work with agents in hybrid group scenarios. In the context of University Learners, the paper outlines how we employ an Ontology of Student Characteristics to personalise information retrieval specifically suited to an individual’s needs. Choice is not a simple “show me your hand and make me a match” but a deliberative artificial intelligence (AI) that uses an ontologically informed agent society to consider the weighted solution paths before choosing the appropriate best. The aim is to enrich the student experience and significantly re-route the student’s journey. The paper uses knowledge-level interoperation of agents to personalise the learning space of students and deliver to them the information and knowledge to suite them best. The aim is to personalise their learning in the presentation/format that is most appropriate for their needs. The paper then generalises this Semantic Technology Framework using shared vocabulary libraries that enable individuals to work in groups with other agents, which might be other people or actually be AIs. The task they undertake is a formal assessment but the interaction mode is one of informal collaboration. Pedagogically this addresses issues of ensuring fairness between students since we can ensure each has the same experience (as provided by the same set of Agents) as each other and an individual mark may be gained. This is achieved by forming a hybrid group of learner and AI Software Agents. Different agent architectures are discussed and a worked example presented. The work here thus aims at fulfilling the student’s needs both in the context of matching their needs but also in allowing them to work in an Agent Based Synthetic Group. This in turn opens us new areas of potential collaborative technology

Using simulation gaming to validate a mathematical modeling platform for resource allocation in disasters

The extraordinary conditions of a disaster require the mobilisation of all available resources, inducing the rush of humanitarian partners into the affected area This phenomenon called the proliferation of actors, causes serious problems during the disaster response phase including the oversupply, duplicated efforts, lack of planning In an attempt to reduce the partner proliferation problem a framework called PREDIS (PREdictive model for DISaster response partner selection) is put forward to configure the humanitarian network within early hours after disaster strike when the information is scarce To verify this model a simulation game is designed using two sets of real decision makers (experts and non-experts) in the disaster Haiyan scenario The result shows that using the PREDIS framework 100% of the experts could make the same decisions less than six hours comparing to 72 hours Also between 71% and 86% of the times experts and non-experts decide similarly using the PREDIS framewor

Situating care in mainstream health economics: an ethical dilemma?

Standard health economics concentrates on the provision of care by medical professionals. Yet ‘care’ receives scant analysis; it is portrayed as a spillover effect or externality in the form of interdependent utility functions. In this context care can only be conceived as either acts of altruism or as social capital. Both conceptions are subject to considerable problems stemming from mainstream health economics’ reliance on a reductionist social model built around instrumental rationality and consequentialism. Subsequently, this implies a disregard for moral rules and duties and the compassionate aspects of behaviour. Care as an externality is a second-order concern relative to self-interested utility maximization, and is therefore crowded out by the parameters of the standard model. We outline an alternative relational approach to conceptualising care based on the social embeddedness of the individual that emphasises the ethical properties of care. The deontological dimension of care suggests that standard health economics is likely to undervalue the importance of care and caring in medicine