title: Interactive concept learning for end-user applications

authors: Maulsby, David

subjects: computer science

abstract: Personalizable software agents will learn new tasks from their users. This implies being able to learn from instructions users might give: examples, yes/no responses, and ambiguous, incomplete hints. Agents should also exploit background knowledge customized for applications such as drawing, word processing and form-filling. The task models that agents learn describe data, actions and their context. Learning about data from examples and hints is the subject of this paper. The Cima learning system combines evidence from examples, task knowledge and user hints to form Disjunctive Normal Form (DNF) rules for classifying, generating or modifying data. Cima's dynamic bias manager generates candidate features (attribute values, functions or relations), from which its DNF learning algorithm selects relevant features and forms the rules. The algorithm is based on a classic greedy method, with two enhancements. First, the standard learning criterion, correct classification, is augmented with a set of utility and instructional criteria. Utility criteria ensure that descriptions are properly formed for use in actions, whether to classify, search for, generate or modify data. Instructional criteria ensure that descriptions include features that users suggest and avoid those that users reject. The second enhancement is to augment the usual statistical metric for selecting relevant attributes with a set of heuristics, including beliefs based on user suggestions and application-specific background knowledge. Using multiple heuristics increases the justification for selecting features; more important, it helps the learner choose among alternative interpretations of hints. When tested on dialogues observed in a prior user study on a simulated interface agent, the learning algorithm achieves 95% of the learning efficiency standard established in that study.

text: Interactive concept learning for end-user applications Personalizable software agents will learn new tasks from their users. This implies being able to learn from instructions users might give: examples, yes/no responses, and ambiguous, incomplete hints. Agents should also exploit background knowledge customized for applications such as drawing, word processing and form-filling. The task models that agents learn describe data, actions and their context. Learning about data from examples and hints is the subject of this paper. The Cima learning system combines evidence from examples, task knowledge and user hints to form Disjunctive Normal Form (DNF) rules for classifying, generating or modifying data. Cima's dynamic bias manager generates candidate features (attribute values, functions or relations), from which its DNF learning algorithm selects relevant features and forms the rules. The algorithm is based on a classic greedy method, with two enhancements. First, the standard learning criterion, correct classification, is augmented with a set of utility and instructional criteria. Utility criteria ensure that descriptions are properly formed for use in actions, whether to classify, search for, generate or modify data. Instructional criteria ensure that descriptions include features that users suggest and avoid those that users reject. The second enhancement is to augment the usual statistical metric for selecting relevant attributes with a set of heuristics, including beliefs based on user suggestions and application-specific background knowledge. Using multiple heuristics increases the justification for selecting features; more important, it helps the learner choose among alternative interpretations of hints. When tested on dialogues observed in a prior user study on a simulated interface agent, the learning algorithm achieves 95% of the learning efficiency standard established in that study.

year: 1995-02

title: A stress-test for democracy: Analysing the New Zealand government's response to the COVID-19 pandemic from a constitutional perspective

authors: Williamson, Myra Elsie Jane Bell

subjects: COVID-19 coronavirus, New Zealand’s constitutional arrangements, freedom of expression and COVID-19, the role of the media and COVID-19, national state of emergency and COVID-19, the Epidemic Response Committee, parliamentary oversight of the executive, COVID-19 investigatory body

abstract: This article explores the New Zealand Government’s response to the COVID-19 coronavirus pandemic through a legal and constitutional lens. It adopts an essentially doctrinal analysis in describing the response but intertwines a comparative law thread, to draw selected comparisons with how other governments have responded. It offers some political, demographical and historical insights to provide background information for non-New Zealand readers. The article aims to provide a comprehensive view of New Zealand’s constitutional arrangements and how they have impacted on the Government’s response to COVID-19 as well as a critical analysis of that response by assessing the effectiveness of various measures adopted by the New Zealand Government. The article consists of six sections. Section one provides an introduction to New Zealand’s constitutional framework including some demographic information for non-New Zealand readers. Section two describes the New Zealand Government’s overall response to the COVID-19 pandemic. Section three discusses the declaration of a national state of emergency. Section four examines the Parliamentary oversight mechanism known as the “Epidemic Response Committee”. Section five explores the role of the media and the importance of upholding the right to freedom of expression when responding to the pandemic. Finally, section six draws out some overall recommendations for New Zealand and other countries to consider when moving forward and preparing for the next pandemic

text: A stress-test for democracy: Analysing the New Zealand government's response to the COVID-19 pandemic from a constitutional perspective This article explores the New Zealand Government’s response to the COVID-19 coronavirus pandemic through a legal and constitutional lens. It adopts an essentially doctrinal analysis in describing the response but intertwines a comparative law thread, to draw selected comparisons with how other governments have responded. It offers some political, demographical and historical insights to provide background information for non-New Zealand readers. The article aims to provide a comprehensive view of New Zealand’s constitutional arrangements and how they have impacted on the Government’s response to COVID-19 as well as a critical analysis of that response by assessing the effectiveness of various measures adopted by the New Zealand Government. The article consists of six sections. Section one provides an introduction to New Zealand’s constitutional framework including some demographic information for non-New Zealand readers. Section two describes the New Zealand Government’s overall response to the COVID-19 pandemic. Section three discusses the declaration of a national state of emergency. Section four examines the Parliamentary oversight mechanism known as the “Epidemic Response Committee”. Section five explores the role of the media and the importance of upholding the right to freedom of expression when responding to the pandemic. Finally, section six draws out some overall recommendations for New Zealand and other countries to consider when moving forward and preparing for the next pandemic

year: 2020

title: A report to iwi on the kaupapa Māori environmental outcomes and indicators kete

authors: Jefferies, Richard

subjects: New Zealand

abstract: Tangata whenua in Aotearoa have been largely excluded from participation in local government  planning since colonisation, but tikanga and Māori values have for the past two decades been acknowledged in resource management and local government legislation, especially the Resource Management Act, 1991 (RMA) and Local Government Act, 2002 (LGA). For example, the RMA has provisions in over 30 sections for councils to give effect to Māori interests.

In practice, however, there is widespread concern that despite these provisions, Māori are largely excluded from local government resource management processes and their values subordinated to those of the wider community, particularly western scientific values.

This report describes research that resulted in a kaupapa Māori outcomes and indicators framework, and associated methods, that can be used by iwi to assess the quality of statutory plans and the environmental performance of councils in their rohe.

text: A report to iwi on the kaupapa Māori environmental outcomes and indicators kete Tangata whenua in Aotearoa have been largely excluded from participation in local government  planning since colonisation, but tikanga and Māori values have for the past two decades been acknowledged in resource management and local government legislation, especially the Resource Management Act, 1991 (RMA) and Local Government Act, 2002 (LGA). For example, the RMA has provisions in over 30 sections for councils to give effect to Māori interests.

In practice, however, there is widespread concern that despite these provisions, Māori are largely excluded from local government resource management processes and their values subordinated to those of the wider community, particularly western scientific values.

This report describes research that resulted in a kaupapa Māori outcomes and indicators framework, and associated methods, that can be used by iwi to assess the quality of statutory plans and the environmental performance of councils in their rohe.

year: 2009-06-30