22,242 research outputs found
KR: An Architecture for Knowledge Representation and Reasoning in Robotics
This paper describes an architecture that combines the complementary
strengths of declarative programming and probabilistic graphical models to
enable robots to represent, reason with, and learn from, qualitative and
quantitative descriptions of uncertainty and knowledge. An action language is
used for the low-level (LL) and high-level (HL) system descriptions in the
architecture, and the definition of recorded histories in the HL is expanded to
allow prioritized defaults. For any given goal, tentative plans created in the
HL using default knowledge and commonsense reasoning are implemented in the LL
using probabilistic algorithms, with the corresponding observations used to
update the HL history. Tight coupling between the two levels enables automatic
selection of relevant variables and generation of suitable action policies in
the LL for each HL action, and supports reasoning with violation of defaults,
noisy observations and unreliable actions in large and complex domains. The
architecture is evaluated in simulation and on physical robots transporting
objects in indoor domains; the benefit on robots is a reduction in task
execution time of 39% compared with a purely probabilistic, but still
hierarchical, approach.Comment: The paper appears in the Proceedings of the 15th International
Workshop on Non-Monotonic Reasoning (NMR 2014
REBA: A Refinement-Based Architecture for Knowledge Representation and Reasoning in Robotics
This paper describes an architecture for robots that combines the
complementary strengths of probabilistic graphical models and declarative
programming to represent and reason with logic-based and probabilistic
descriptions of uncertainty and domain knowledge. An action language is
extended to support non-boolean fluents and non-deterministic causal laws. This
action language is used to describe tightly-coupled transition diagrams at two
levels of granularity, with a fine-resolution transition diagram defined as a
refinement of a coarse-resolution transition diagram of the domain. The
coarse-resolution system description, and a history that includes (prioritized)
defaults, are translated into an Answer Set Prolog (ASP) program. For any given
goal, inference in the ASP program provides a plan of abstract actions. To
implement each such abstract action, the robot automatically zooms to the part
of the fine-resolution transition diagram relevant to this action. A
probabilistic representation of the uncertainty in sensing and actuation is
then included in this zoomed fine-resolution system description, and used to
construct a partially observable Markov decision process (POMDP). The policy
obtained by solving the POMDP is invoked repeatedly to implement the abstract
action as a sequence of concrete actions, with the corresponding observations
being recorded in the coarse-resolution history and used for subsequent
reasoning. The architecture is evaluated in simulation and on a mobile robot
moving objects in an indoor domain, to show that it supports reasoning with
violation of defaults, noisy observations and unreliable actions, in complex
domains.Comment: 72 pages, 14 figure
Representations of world coordinates in FITS
The initial descriptions of the FITS format provided a simplified method for
describing the physical coordinate values of the image pixels, but deliberately
did not specify any of the detailed conventions required to convey the
complexities of actual image coordinates. Building on conventions in wide use
within astronomy, this paper proposes general extensions to the original
methods for describing the world coordinates of FITS data. In subsequent
papers, we apply these general conventions to the methods by which spherical
coordinates may be projected onto a two-dimensional plane and to
frequency/wavelength/velocity coordinates.Comment: 15 Pages, 1 figure, LaTex with Astronomy & Astrophysics macro
package, submitted to A&A, related papers at
http://www.aoc.nrao.edu/~egreise
JaxoDraw: A graphical user interface for drawing Feynman diagrams. Version 2.0 release notes
A new version of the Feynman graph plotting tool JaxoDraw is presented.
Version 2.0 is a fundamental re-write of most of the JaxoDraw core and some
functionalities, in particular importing graphs, are not backward-compatible
with the 1.x branch. The most prominent new features include: drawing of Bezier
curves for all particle modes, on-the-fly update of edited objects, multiple
undo/redo functionality, the addition of a plugin infrastructure, and a general
improved memory performance. A new LaTeX style file is presented that has been
written specifically on top of the original axodraw.sty to meet the needs of
this this new version.Comment: 17 pages, 1 figur
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Expressive Policy Analysis with Enhanced System Dynamicity
Despite several research studies, the effective analysis of policy based systems remains a significant challenge. Policy analysis should at least (i) be expressive (ii) take account of obligations and authorizations, (iii) include a dynamic system model, and (iv) give useful diagnostic information. We present a logic-based policy analysis framework which satisfies these requirements, showing how many significant policy-related properties can be analysed, and we give details of a prototype implementation. Copyright 2009 ACM
HUD Homes: How they Can Promote Home Ownership and Reduce House Abandonment
For many, the American Dream still means owning a home. The home ownership rate in the U.S. fell in the fourth quarter of 2007 to its lowest level since the beginning of 2002--this from a record high in the middle of 2004. What is more alarming, however, is that the home owner vacancy rate went up 2.8 percent. The bulk of the vacant homes are foreclosed homes. Among such foreclosed homes are Department of Housing and Urban Development (HUD) homes that have come into HUDās possession as a result of Federal Housing Administration (FHA) loan defaults
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