136 research outputs found
A Universal Machine for Biform Theory Graphs
Broadly speaking, there are two kinds of semantics-aware assistant systems
for mathematics: proof assistants express the semantic in logic and emphasize
deduction, and computer algebra systems express the semantics in programming
languages and emphasize computation. Combining the complementary strengths of
both approaches while mending their complementary weaknesses has been an
important goal of the mechanized mathematics community for some time. We pick
up on the idea of biform theories and interpret it in the MMTt/OMDoc framework
which introduced the foundations-as-theories approach, and can thus represent
both logics and programming languages as theories. This yields a formal,
modular framework of biform theory graphs which mixes specifications and
implementations sharing the module system and typing information. We present
automated knowledge management work flows that interface to existing
specification/programming tools and enable an OpenMath Machine, that
operationalizes biform theories, evaluating expressions by exhaustively
applying the implementations of the respective operators. We evaluate the new
biform framework by adding implementations to the OpenMath standard content
dictionaries.Comment: Conferences on Intelligent Computer Mathematics, CICM 2013 The final
publication is available at http://link.springer.com
A Foundational View on Integration Problems
The integration of reasoning and computation services across system and
language boundaries is a challenging problem of computer science. In this
paper, we use integration for the scenario where we have two systems that we
integrate by moving problems and solutions between them. While this scenario is
often approached from an engineering perspective, we take a foundational view.
Based on the generic declarative language MMT, we develop a theoretical
framework for system integration using theories and partial theory morphisms.
Because MMT permits representations of the meta-logical foundations themselves,
this includes integration across logics. We discuss safe and unsafe integration
schemes and devise a general form of safe integration
Using dialogue to learn math in the LeActiveMath project
We describe a tutorial dialogue system under development that assists students in learning how to differentiate equations. The system uses deep natural language understanding and generation to both interpret students â utterances and automatically generate a response that is both mathematically correct and adapted pedagogically and linguistically to the local dialogue context. A domain reasoner provides the necessary knowledge about how students should approach math problems as well as their (in)correctness, while a dialogue manager directs pedagogical strategies and keeps track of what needs to be done to keep the dialogue moving along.
Technologies for teaching mathematics via the world wide web
Published ArticleThis paper tries to find answers to the question concerning the availability of suitable technologies to accommodate the teaching and learning of mathematics by means of the World Wide Web. It addresses three standards for the presentation of content mark-up and touches on the importance of adequate browser applicability with respect to MathML as one of the standards. Various tools for rendering MathML on the web, as well as plug-ins and extensions and other combinations of technologies, are discussed. The paper concludes with the introduction of a dynamic mathematics object model (DMOM) by Robert Miner from Design Science Inc. Requirements for a DMOM are formulated and its implementation is discussed
OpenMath and SMT-LIB
OpenMath and SMT-LIB are languages with very different origins, but both
"represent mathematics". We describe SMT-LIB for the OpenMath community and
consider adaptations for both languages to support the growing SC-Square
initiative.Comment: Presented in the OpenMath 2017 Workshop, at CICM 2017, Edinburgh, U
Generic access to symbolic computing services
Symbolic computation is one of the computational domains that requires large computational
resources. Computer Algebra Systems (CAS), the main tools used for symbolic
computations, are mainly designed to be used as software tools installed on standalone
machines that do not provide the required resources for solving large symbolic computation
problems. In order to support symbolic computations an infrastructure built upon
massively distributed computational environments must be developed.
Building an infrastructure for symbolic computations requires a thorough analysis of
the most important requirements raised by the symbolic computation world and must
be built based on the most suitable architectural styles and technologies. The architecture
that we propose is composed of several main components: the Computer Algebra
System (CAS) Server that exposes the functionality implemented by one or more supporting
CASs through generic interfaces of Grid Services; the Architecture for Grid
Symbolic Services Orchestration (AGSSO) Server that allows seamless composition of
CAS Server capabilities; and client side libraries to assist the users in describing workflows
for symbolic computations directly within the CAS environment. We have also
designed and developed a framework for automatic data management of mathematical
content that relies on OpenMath encoding.
To support the validation and fine tuning of the system we have developed a simulation
platform that mimics the environment on which the architecture is deployed
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