Research in Action 2008 - University of Toronto

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16 Interactive Performance Control – A New Puppetry of Real and Virtual Robots Project Team Eugene Fiume Faculty Joe Laszlo* Graduate Student Michiel van de Panne Associate Faculty, University of British Columbia From video games to feature films, the laws of physics play an increasing role in creating the compelling animation modern audiences demand. Animating agile, physically realistic characters, however, is as much art as it is science, whether the characters are inhabitants of fantastical virtual worlds, real robotic competitors running in a soccer stadium, or mechanical family pets. Current approaches to making such creatures move about nimbly focus on the use of large motion databases, genetically-inspired learning algorithms, or meticulously crafted, but often brittle, custom programming. In contrast, our approach puts the reins directly into the hands of the animator, who becomes an interactive performer, vicariously flexing a character’s muscles or motors, moment-to-moment, to make it run and jump about under its own power, a “stringless puppet” in a potential new performance art form. We present a variety of simple but compelling examples of animated characters “performed” in this fashion, and argue the approach to be a viable form of physics-based animation, engaging and entertaining to performer and audience alike. Building Software With Traceability Traceability is a highly desirable property for all types of software systems. However, due to the costs associated with conventional after-the-fact traceability approaches, it is practiced only in cases such as safety-critical systems where cost minimization is not a concern. Our primary goal is to make traceability an economically feasible option for all types of software systems, including business applications. In contrast to conventional approaches, our approach is proactive and based on the definition and enforcement of a set of project-specific evolution invariants (a.k.a “regularities”) that prescribe the mapping between source code entities and other trace endpoints such as requirements. Our approach to traceability can be seamlessly integrated with current widely-used iterative development methodologies such XP and RUP. Project Team Dave Wortman Faculty Arbi Ghazarian* Graduate Student 18 19 www.cs.toronto.edu
16 A Content Delivery System for Bluetooth Project Team Stefan Saroiu* Faculty Tim Smith Graduate Student We have constructed a system for news and advertisement delivery to Bluetooth-enabled mobile devices, which we have recently evaluated at Toronto’s Eaton Centre. In the span of four hours, we were able to transmit a total of 136MB worth of content to over three hundred devices. We have also developed a tool for the evaluation of Bluetooth systems, and can use this tool to perform a live evaluation of our content delivery system to discoverable Bluetooth devices present in a given area. Interactive Preference Elicitation We present a system for performing multiattribute product search in large product catalogs or constrained spaces of billions of configurations. Our software tool automates the role of a decision analyst: it guides a user through a series of interactions and queries, and then recommends a decision based on acquired preference information. By asking direct preference queries, we can effectively balance the tradeoff between elicitation costs (such as the time and effort required to answer queries) and the quality of the recommended option (measured in terms of possible regret of choosing that option). Our particular proof-of-concept domain is apartment search in Toronto; however, the system can be configured to support a variety of other multiattribute domains, from travel planning to procurement. Our research goal is to create intelligent systems that provide users with automated decision support. By using flexible utility models to capture quantitative preferences and devising intelligent strategies for eliciting such preferences based on novel robust optimization methods, we can deal with large and complex domains in which standard search techniques are either infeasible or too costly. Project Team Craig Boutilier* Faculty Darius Braziunas Graduate Student 20 21 www.cs.toronto.edu
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Research in Action 2008 - University of Toronto

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