57,408 research outputs found
Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids
Real-life control tasks involve matters of various substances---rigid or soft
bodies, liquid, gas---each with distinct physical behaviors. This poses
challenges to traditional rigid-body physics engines. Particle-based simulators
have been developed to model the dynamics of these complex scenes; however,
relying on approximation techniques, their simulation often deviates from
real-world physics, especially in the long term. In this paper, we propose to
learn a particle-based simulator for complex control tasks. Combining learning
with particle-based systems brings in two major benefits: first, the learned
simulator, just like other particle-based systems, acts widely on objects of
different materials; second, the particle-based representation poses strong
inductive bias for learning: particles of the same type have the same dynamics
within. This enables the model to quickly adapt to new environments of unknown
dynamics within a few observations. We demonstrate robots achieving complex
manipulation tasks using the learned simulator, such as manipulating fluids and
deformable foam, with experiments both in simulation and in the real world. Our
study helps lay the foundation for robot learning of dynamic scenes with
particle-based representations.Comment: Accepted to ICLR 2019. Project Page: http://dpi.csail.mit.edu Video:
https://www.youtube.com/watch?v=FrPpP7aW3L
COST Action IC 1402 ArVI: Runtime Verification Beyond Monitoring -- Activity Report of Working Group 1
This report presents the activities of the first working group of the COST
Action ArVI, Runtime Verification beyond Monitoring. The report aims to provide
an overview of some of the major core aspects involved in Runtime Verification.
Runtime Verification is the field of research dedicated to the analysis of
system executions. It is often seen as a discipline that studies how a system
run satisfies or violates correctness properties. The report exposes a taxonomy
of Runtime Verification (RV) presenting the terminology involved with the main
concepts of the field. The report also develops the concept of instrumentation,
the various ways to instrument systems, and the fundamental role of
instrumentation in designing an RV framework. We also discuss how RV interplays
with other verification techniques such as model-checking, deductive
verification, model learning, testing, and runtime assertion checking. Finally,
we propose challenges in monitoring quantitative and statistical data beyond
detecting property violation
Genetic Improvement of Software: a Comprehensive Survey
Genetic improvement (GI) uses automated search to find improved versions of existing software. We present a comprehensive survey of this nascent field of research with a focus on the core papers in the area published between 1995 and 2015. We identified core publications including empirical studies, 96% of which use evolutionary algorithms (genetic programming in particular). Although we can trace the foundations of GI back to the origins of computer science itself, our analysis reveals a significant upsurge in activity since 2012. GI has resulted in dramatic performance improvements for a diverse set of properties such as execution time, energy and memory consumption, as well as results for fixing and extending existing system functionality. Moreover, we present examples of research work that lies on the boundary between GI and other areas, such as program transformation, approximate computing, and software repair, with the intention of encouraging further exchange of ideas between researchers in these fields
Applied Evaluative Informetrics: Part 1
This manuscript is a preprint version of Part 1 (General Introduction and
Synopsis) of the book Applied Evaluative Informetrics, to be published by
Springer in the summer of 2017. This book presents an introduction to the field
of applied evaluative informetrics, and is written for interested scholars and
students from all domains of science and scholarship. It sketches the field's
history, recent achievements, and its potential and limits. It explains the
notion of multi-dimensional research performance, and discusses the pros and
cons of 28 citation-, patent-, reputation- and altmetrics-based indicators. In
addition, it presents quantitative research assessment as an evaluation
science, and focuses on the role of extra-informetric factors in the
development of indicators, and on the policy context of their application. It
also discusses the way forward, both for users and for developers of
informetric tools.Comment: The posted version is a preprint (author copy) of Part 1 (General
Introduction and Synopsis) of a book entitled Applied Evaluative
Bibliometrics, to be published by Springer in the summer of 201
Incremental and Modular Context-sensitive Analysis
Context-sensitive global analysis of large code bases can be expensive, which
can make its use impractical during software development. However, there are
many situations in which modifications are small and isolated within a few
components, and it is desirable to reuse as much as possible previous analysis
results. This has been achieved to date through incremental global analysis
fixpoint algorithms that achieve cost reductions at fine levels of granularity,
such as changes in program lines. However, these fine-grained techniques are
not directly applicable to modular programs, nor are they designed to take
advantage of modular structures. This paper describes, implements, and
evaluates an algorithm that performs efficient context-sensitive analysis
incrementally on modular partitions of programs. The experimental results show
that the proposed modular algorithm shows significant improvements, in both
time and memory consumption, when compared to existing non-modular, fine-grain
incremental analysis techniques. Furthermore, thanks to the proposed
inter-modular propagation of analysis information, our algorithm also
outperforms traditional modular analysis even when analyzing from scratch.Comment: 56 pages, 27 figures. To be published in Theory and Practice of Logic
Programming. v3 corresponds to the extended version of the ICLP2018 Technical
Communication. v4 is the revised version submitted to Theory and Practice of
Logic Programming. v5 (this one) is the final author version to be published
in TPL
Program Synthesis using Natural Language
Interacting with computers is a ubiquitous activity for millions of people.
Repetitive or specialized tasks often require creation of small, often one-off,
programs. End-users struggle with learning and using the myriad of
domain-specific languages (DSLs) to effectively accomplish these tasks.
We present a general framework for constructing program synthesizers that
take natural language (NL) inputs and produce expressions in a target DSL. The
framework takes as input a DSL definition and training data consisting of
NL/DSL pairs. From these it constructs a synthesizer by learning optimal
weights and classifiers (using NLP features) that rank the outputs of a
keyword-programming based translation. We applied our framework to three
domains: repetitive text editing, an intelligent tutoring system, and flight
information queries. On 1200+ English descriptions, the respective synthesizers
rank the desired program as the top-1 and top-3 for 80% and 90% descriptions
respectively
Enhancing Predicate Pairing with Abstraction for Relational Verification
Relational verification is a technique that aims at proving properties that
relate two different program fragments, or two different program runs. It has
been shown that constrained Horn clauses (CHCs) can effectively be used for
relational verification by applying a CHC transformation, called predicate
pairing, which allows the CHC solver to infer relations among arguments of
different predicates. In this paper we study how the effects of the predicate
pairing transformation can be enhanced by using various abstract domains based
on linear arithmetic (i.e., the domain of convex polyhedra and some of its
subdomains) during the transformation. After presenting an algorithm for
predicate pairing with abstraction, we report on the experiments we have
performed on over a hundred relational verification problems by using various
abstract domains. The experiments have been performed by using the VeriMAP
transformation and verification system, together with the Parma Polyhedra
Library (PPL) and the Z3 solver for CHCs.Comment: Pre-proceedings paper presented at the 27th International Symposium
on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur,
Belgium, 10-12 October 2017 (arXiv:1708.07854
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