53,131 research outputs found
Towards an Intelligent Tutor for Mathematical Proofs
Computer-supported learning is an increasingly important form of study since
it allows for independent learning and individualized instruction. In this
paper, we discuss a novel approach to developing an intelligent tutoring system
for teaching textbook-style mathematical proofs. We characterize the
particularities of the domain and discuss common ITS design models. Our
approach is motivated by phenomena found in a corpus of tutorial dialogs that
were collected in a Wizard-of-Oz experiment. We show how an intelligent tutor
for textbook-style mathematical proofs can be built on top of an adapted
assertion-level proof assistant by reusing representations and proof search
strategies originally developed for automated and interactive theorem proving.
The resulting prototype was successfully evaluated on a corpus of tutorial
dialogs and yields good results.Comment: In Proceedings THedu'11, arXiv:1202.453
Synthesizing Probabilistic Invariants via Doob's Decomposition
When analyzing probabilistic computations, a powerful approach is to first
find a martingale---an expression on the program variables whose expectation
remains invariant---and then apply the optional stopping theorem in order to
infer properties at termination time. One of the main challenges, then, is to
systematically find martingales.
We propose a novel procedure to synthesize martingale expressions from an
arbitrary initial expression. Contrary to state-of-the-art approaches, we do
not rely on constraint solving. Instead, we use a symbolic construction based
on Doob's decomposition. This procedure can produce very complex martingales,
expressed in terms of conditional expectations.
We show how to automatically generate and simplify these martingales, as well
as how to apply the optional stopping theorem to infer properties at
termination time. This last step typically involves some simplification steps,
and is usually done manually in current approaches. We implement our techniques
in a prototype tool and demonstrate our process on several classical examples.
Some of them go beyond the capability of current semi-automatic approaches
Extending ACL2 with SMT Solvers
We present our extension of ACL2 with Satisfiability Modulo Theories (SMT)
solvers using ACL2's trusted clause processor mechanism. We are particularly
interested in the verification of physical systems including Analog and
Mixed-Signal (AMS) designs. ACL2 offers strong induction abilities for
reasoning about sequences and SMT complements deduction methods like ACL2 with
fast nonlinear arithmetic solving procedures. While SAT solvers have been
integrated into ACL2 in previous work, SMT methods raise new issues because of
their support for a broader range of domains including real numbers and
uninterpreted functions. This paper presents Smtlink, our clause processor for
integrating SMT solvers into ACL2. We describe key design and implementation
issues and describe our experience with its use.Comment: In Proceedings ACL2 2015, arXiv:1509.0552
Multifaceted companion devices: applying the new model of media attendance to smartphone usage
This study inspects the relationship between outcome expectations, habit strength, and smartphone usage by attempting to validate the new model of media attendance (NMMA) (LaRose and Eastin, 2004) , a social-cognitive theory of uses and gratifications. The fast adoption rate of smartphones, and their inherent characteristics as convergent, always-on, always-connected devices, warrant a closer look into user habitualization of this medium. Using a sample of 481 smartphone users selected from a larger panel, we were able to support the NMMA, although surprisingly no significant effect of habit strength on smartphone usage was found. While some uncertainties connected to the method are noted, this suggests a more complex reality, in which habitualization of a convergent media device does not necessarily implicate a significant rise in usage
Sphenomenology --- An Overview, with a Focus on a Higgsino LSP World, and on Eventual Tests of String Theory
In this talk, as requested, I begin with a overview and with some basic
reminders about how evidence for supersymmetry in nature might appear -- in
particular, how SUSY signatures are never clear so it is difficult to search
for them without major theoretical input. Models can be usefully categorized
phenomenologically by naming their LSP -- that is, once the LSP is
approximately fixed so is the behavior of the observables, and the resulting
behavior is generally very different for different LSPs. Next I compare the
three main LSP-models (gravitino, bino, higgsino). Hints from data suggest
taking the higgsino-LSP world very seriously, so I focus on it, and describe
its successful prediction of reported events from the 1996 LEP runs. SUSY
signatures in the LSP world are very different from those that are
usually studied. Then I briefly discuss how to measure the parameters of the
effective Lagrangian from collider and decay data. Finally I turn to how data
will test and help extract the implications of string theories.Comment: Uses espcrc2.st
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