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Recovering from errors during programming by demonstration

Recovering from errors during programming by demonstration,10.1145/1378773.1378794,Jiun-hung Chen,Daniel S. Weld

Recovering from errors during programming by demonstration   (Citations: 8)
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Many end-users wish to customize their applications, au- tomating common tasks and routines. Unfortunately, this automation is difficult today — users must choose between brittle macros and complex scripting languages. Program- ming by demonstration (PBD) offers a middle ground, al- lowing users to demonstrate a procedure multiple times and generalizing the requisite behavior with machine learning. Unfortunately, many PBD systems are almost as brittle as macro recorders, offering few ways for a user to control the learning process or correct the demonstrations used as training examples. This paper presents CHINLE, a system which automatically constructs PBD systems for applica- tions based on their interface specification. The resulting PBD systems have novel interaction and visualization meth- ods, which allow the user to easily monitor and guide the learning process, facilitating error recovery during training. CHINLE-constructedPBDsystemslearnprocedureswithcon- ditionals and perform partial learning if the procedure is too complex to learn completely.
Conference: Intelligent User Interfaces - IUI , pp. 159-168, 2008
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    • ...It is also desirable because humans typically combine bothmethods when teaching complex procedures, either demonstrating first and then describing the general case or describing the procedure first and then demonstrating it. There have been some promising approaches for making PbD systems more robust to errors and allowing user editsinterleaved withdemonstrations (e.g., [19, 4])...
    • ...CHINLE [4] is a system that generates domain specific PbD systems from declarative interface specifications...

    Christian Fritzet al. A formal framework for combining natural instruction and demonstration...

    • ...Exemplar focuses on exposing an intelligible and editable visualization of its model, addressing the fact that automatically learned models are often inscrutable [5,18]...
    • ...Verifying Specifications. Past work has shown that end-users must be able to verify that a specification works as intended [5,18]...
    • ...It is much less straightforward in PBD systems [5], and may require that entirely new sets of demonstrations be recorded...

    Evan Welbourneet al. Specification and Verification of Complex Location Events with Panoram...

    • ...Chen and Weld developed CHINLE, a learning system that incorporates techniques for handling errors in demonstrations within widget-based interfaces [1]...

    Eugene R. Creswicket al. Error-tolerant version space algebra

    • ...Recent work with PBD systems also relates to debugging machinelearned programs [6], but their technique allows the user to retract actions in a demonstration, which results in adding missing values to the training data rather than directly modifying the classifier's logic Thus, in summary, the ability of end users to interactively debug the machine-learned logic has so far been quite limited...

    Todd Kuleszaet al. Fixing the program my computer learned: barriers for end users, challe...

    • ...[9, 10]) requires much understanding from the end-user and poses high additional interaction costs, but induces trust in the provided support as it can be controlled by the user...

    Melanie Hartmannet al. AUGUR: providing context-aware interaction support

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