4 resultados para Learning in multi-agent systems

em University of Southampton, United Kingdom


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Abstract Reputation, influenced by ratings from past clients, is crucial for providers competing for custom. For new providers with less track record, a few negative ratings can harm their chances of growing. In the JASPR project, we aim to look at how to ensure automated reputation assessments are justified and informative. Even an honest balanced review of a service provision may still be an unreliable predictor of future performance if the circumstances differ. For example, a service may have previously relied on different sub-providers to now, or been affected by season-specific weather events. A common way to ameliorate the ratings that may not reflect future performance is by weighting by recency. We argue that better results are obtained by querying provenance records on how services are provided for the circumstances of provision, to determine the significance of past interactions. Informed by case studies in global logistics, taxi hire, and courtesy car leasing, we are going on to explore the generation of explanations for reputation assessments, which can be valuable both for clients and for providers wishing to improve their match to the market, and applying machine learning to predict aspects of service provision which may influence decisions on the appropriateness of a provider. In this talk, I will give an overview of the research conducted and planned on JASPR. Speaker Biography Dr Simon Miles Simon Miles is a Reader in Computer Science at King's College London, UK, and head of the Agents and Intelligent Systems group. He conducts research in the areas of normative systems, data provenance, and medical informatics at King's, and has published widely and manages a number of research projects in these areas. He was previously a researcher at the University of Southampton after graduating from his PhD at Warwick. He has twice been an organising committee member for the Autonomous Agents and Multi-Agent Systems conference series, and was a member of the W3C working group which published standards on interoperable provenance data in 2013.

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The UK Professional Standards Framework (UK PSF) for teaching and supporting learning, launched in February 2006, is a flexible framework which uses a descriptor-based approach to professional standards. There are three standard descriptors each of which is applicable to a number of staff roles and to different career stages of those engaged in teaching and supporting learning. The standard descriptors are underpinned by areas of professional activity, core knowledge and professional values. The framework provides a reference point for institutions and individuals as well as supporting ongoing development within any one standard descriptor.

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This is a part of a collection of materials developed by the HEAcademy Subject Centre for Languages, linguistics and area studies. The materials provide reflective activities designed to engage teachers with some of the key issues in working with international students and practical ideas for ways in which these can be addressed. They will be of particular interest to new staff or anyone new to working with international students.