Optimising ITS behaviour with Bayesian networks and decision theory

We propose and demonstrate a methodology for building tractable normative intelligent tutoring systems (ITSs). A normative ITS uses a Bayesian network for long-term student modelling and decision theory to select the next tutorial action. Because normative theories are a general framework for rational behaviour, they can be used to both define and apply learning theories in a rational, and therefore optimal, way. This contrasts to the more traditional approach of using an ad-hoc scheme to implement the learning theory. A key step of the methodology is the induction and the continual adaptation of the Bayesian network student model from student performance data, a step that is distinct from other recent Bayesian net approaches in which the network structure and probabilities are either chosen beforehand by an expert, or by efficiency considerations. The methodology is demonstrated by a description and evaluation of CAPIT, a normative constraint-based tutor for English capitalisation and punctuation. Our evaluation results show that a class using the full normative version of CAPIT learned the domain rules at a faster rate than the class that used a non-normative version of the same system

USEM: A ubiquitous smart energy management system for residential homes

With the ever-increasing worldwide demand for energy, and the limited available energy resources, there is a growing need to reduce our energy consumption whenever possible. Therefore, over the past few decades a range of technologies have been proposed to assist consumers with reducing their energy use. Most of these have focused on decreasing energy consumption in the industry, transport, and services sectors. In more recent years, however, growing attention has been given to energy use in the residential sector, which accounts for nearly 30% of total energy consumption in the developed countries. Here we present one such system, which aims to assist residential users with monitoring their energy usage and provides mechanisms for setting up and controlling their home appliances to conserve energy. We also describe a user study we have conducted to evaluate the effectiveness of this system in supporting its users with a range of tools and visualizations developed for ubiquitous devices such as mobile phones and tablets. The findings of this study have shown the potential benefits of our system, and have identified areas of improvement that need to be addressed in the future

Topics in social network analysis and network science

This chapter introduces statistical methods used in the analysis of social networks and in the rapidly evolving parallel-field of network science. Although several instances of social network analysis in health services research have appeared recently, the majority involve only the most basic methods and thus scratch the surface of what might be accomplished. Cutting-edge methods using relevant examples and illustrations in health services research are provided

Lessons in Using Vibrotactile Feedback to Guide Fast Arm Motions

We present and evaluate an arm-motion guidance system that uses magnetic tracking sensors and low cost vibrotactile actuators. The system measures the movement of the user’s arm and provides vibration feedback at the wrist and elbow when they stray from the desired motion. An initial study was conducted to investigate whether adding tactile feedback to visual feedback reduces motion errors when a user is learning a new arm trajectory. Although subjects preferred it, we found that the addition of tactile feedback did not affect motion tracking performance. We also found no strong preference or performance differences between attractive and repulsive tactile feedback. Some factors that may have influenced these results include the speed and the complexity of the tested motions, the type of tactile actuators and drive signals used, and inconsistencies in joint angle estimation due to Euler angle gimbal lock. We discuss insights from this analysis and provide suggestions for future systems and studies in tactile motion guidance

The Navigability of Strong Ties: Small Worlds, Tie Strength and Network Topology

International audienceWe examine data on and models of small world properties and parameters of social networks. Our focus, on tie-strength, multilevel networks and searchability in strong-tie social networks, allows us to extend some of the questions and findings of recent research and the fit of small world models to sociological and anthropological data on human communities. We offer a 'navigability of strong ties' hypothesis about network topologies tested with data from kinship systems, but potentially applicable to corporate cultures and business networks

Ending Child Marriage in a Generation: What Research is Needed?

In recent years, the obstacles that child marriage poses to development and to the achievement of the Millennium Development Goals have been widely recognized. Varied responses to the problem have been devised. The number of programs testing different approaches to ending child marriage has grown, and many have been evaluated. We are starting to get a sense of what works and the general areas in which investing in research could make a difference.The purpose of this paper is to identify gaps in the research on child marriage in which additional investment could catalyze change. Much remains to understand about child marriage and how to influence it. By mapping out current knowledge of child marriage and the programs designed to address it, and by highlighting questions to which we do not yet know the answers, the paper is intended to generate discussion in the field and clarify what we need to know to bring an end to this deeply harmful practice.The paper also moves us closer to the development of a shared theory of change for this field: given that many organizations are now working in this area, how can their programs and related research be understood -- aligned -- in such a way that their work feeds into a single theory of change?The research gaps on their own should not drive investments in child marriage. A worthy research mandate must also be driven by programmatic and advocacy needs. The recommended areas for research are not meant to provide a definitive menu, but rather to describe the general contours of what we know and what we need to understand better

Learning to Predict Combinatorial Structures

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions to ensure efficient, polynomial time estimation of model parameters. For several combinatorial structures, including cycles, partially ordered sets, permutations and other graph classes, these assumptions do not hold. In this thesis, we address the problem of designing learning algorithms for predicting combinatorial structures by introducing two new assumptions: (i) The first assumption is that a particular counting problem can be solved efficiently. The consequence is a generalisation of the classical ridge regression for structured prediction. (ii) The second assumption is that a particular sampling problem can be solved efficiently. The consequence is a new technique for designing and analysing probabilistic structured prediction models. These results can be applied to solve several complex learning problems including but not limited to multi-label classification, multi-category hierarchical classification, and label ranking.Comment: PhD thesis, Department of Computer Science, University of Bonn (submitted, December 2009

05011 Abstracts Collection -- Computing and Markets

From 03.01.05 to 07.01.05, the Dagstuhl Seminar 05011``Computing and Markets\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available