76,410 research outputs found
Scheme-based theorem discovery and concept invention
In this thesis we describe an approach to automatically invent/explore new mathematical
theories, with the goal of producing results comparable to those produced by humans,
as represented, for example, in the libraries of the Isabelle proof assistant. Our
approach is based on ‘schemes’, which are formulae in higher-order logic. We show
that it is possible to automate the instantiation process of schemes to generate conjectures
and definitions. We also show how the new definitions and the lemmata discovered
during the exploration of a theory can be used, not only to help with the proof
obligations during the exploration, but also to reduce redundancies inherent in most
theory-formation systems. We exploit associative-commutative (AC) operators using
ordered rewriting to avoid AC variations of the same instantiation. We implemented
our ideas in an automated tool, called IsaScheme, which employs Knuth-Bendix completion
and recent automatic inductive proof tools. We have evaluated our system in a
theory of natural numbers and a theory of lists
Hipster: Integrating Theory Exploration in a Proof Assistant
This paper describes Hipster, a system integrating theory exploration with
the proof assistant Isabelle/HOL. Theory exploration is a technique for
automatically discovering new interesting lemmas in a given theory development.
Hipster can be used in two main modes. The first is exploratory mode, used for
automatically generating basic lemmas about a given set of datatypes and
functions in a new theory development. The second is proof mode, used in a
particular proof attempt, trying to discover the missing lemmas which would
allow the current goal to be proved. Hipster's proof mode complements and
boosts existing proof automation techniques that rely on automatically
selecting existing lemmas, by inventing new lemmas that need induction to be
proved. We show example uses of both modes
Exploring individual user differences in the 2D/3D interaction with medical image data
User-centered design is often performed without regard to individual user differences. In this paper, we report results of an empirical study aimed to evaluate whether computer experience and demographic user characteristics would have an effect on the way people interact with the visualized medical data in a 3D virtual environment using 2D and 3D input devices. We analyzed the interaction through performance data, questionnaires and observations. The results suggest that differences in gender, age and game experience have an effect on people’s behavior and task performance, as well as on subjective\ud
user preferences
Reasoning about order errors in interaction
Reliability of an interactive system depends on users as well as the device implementation. User errors can result in catastrophic system
failure. However, work from the field of cognitive science shows that
systems can be designed so as to completely eliminate whole classes of
user errors. This means that user errors should also fall within the remit
of verification methods. In this paper we demonstrate how the HOL
theorem prover [7] can be used to detect and prove the absence of the
family of errors known as order errors. This is done by taking account
of the goals and knowledge of users. We provide an explicit generic user
model which embodies theory from the cognitive sciences about the way
people are known to act. The user model describes action based on user
communication goals. These are goals that a user adopts based on their
knowledge of the task they must perform to achieve their goals. We use
a simple example of a vending machine to demonstrate the approach.
We prove that a user does achieve their goal for a particular design of
machine. In doing so we demonstrate that communication goal based
errors cannot occur
Layout of Multiple Views for Volume Visualization: A User Study
Abstract. Volume visualizations can have drastically different appearances when viewed using a variety of transfer functions. A problem then occurs in trying to organize many different views on one screen. We conducted a user study of four layout techniques for these multiple views. We timed participants as they separated different aspects of volume data for both time-invariant and time-variant data using one of four different layout schemes. The layout technique had no impact on performance when used with time-invariant data. With time-variant data, however, the multiple view layouts all resulted in better times than did a single view interface. Surprisingly, different layout techniques for multiple views resulted in no noticeable difference in user performance. In this paper, we describe our study and present the results, which could be used in the design of future volume visualization software to improve the productivity of the scientists who use it
Space exploration: The interstellar goal and Titan demonstration
Automated interstellar space exploration is reviewed. The Titan demonstration mission is discussed. Remote sensing and automated modeling are considered. Nuclear electric propulsion, main orbiting spacecraft, lander/rover, subsatellites, atmospheric probes, powered air vehicles, and a surface science network comprise mission component concepts. Machine, intelligence in space exploration is discussed
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Automation in distance learning: an empirical study of unlearning and academic identity change linked to automation of student messaging within distance learning
This paper explores the unlearning and learning undertaken by adjuncts (Associate Lecturers) during the introduction of automated messaging by the university as part replacement of adjunct pastoral support for students. Automated messages were introduced by the University to standardize the student experience in terms of qualification communications, for example, reminders of forthcoming assessment deadlines. This change in communicative strategy is due to shifting power from a collegial to a managerial culture and practice in supporting distance learning students effectively. This is a university-wide initiative in a bid to improve progression and completion in an increasingly cost-focused higher education environment. The introduction of automated messaging requires adjuncts to learn new processes, and thus unlearn previous organizational routines which impacts upon their academic identity and perceived power within their roles
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