313 research outputs found
Modeling Human Ad Hoc Coordination
Whether in groups of humans or groups of computer agents, collaboration is
most effective between individuals who have the ability to coordinate on a
joint strategy for collective action. However, in general a rational actor will
only intend to coordinate if that actor believes the other group members have
the same intention. This circular dependence makes rational coordination
difficult in uncertain environments if communication between actors is
unreliable and no prior agreements have been made. An important normative
question with regard to coordination in these ad hoc settings is therefore how
one can come to believe that other actors will coordinate, and with regard to
systems involving humans, an important empirical question is how humans arrive
at these expectations. We introduce an exact algorithm for computing the
infinitely recursive hierarchy of graded beliefs required for rational
coordination in uncertain environments, and we introduce a novel mechanism for
multiagent coordination that uses it. Our algorithm is valid in any environment
with a finite state space, and extensions to certain countably infinite state
spaces are likely possible. We test our mechanism for multiagent coordination
as a model for human decisions in a simple coordination game using existing
experimental data. We then explore via simulations whether modeling humans in
this way may improve human-agent collaboration.Comment: AAAI 201
Focal Plane Geometry Characterization of the Kepler Mission
The Kepler Mission focal plane contains 42 charge-coupled device (CCD) photodetectors. Each CCD is composed of 2.2 million square pixels, 27 micrometers on a side, arranged in a grid of 2,200 columns by 1,044 rows. The science goals of the Kepler Mission require that the position of each CCD be determined with an accuracy of 0.1 pixels, corresponding to 2.7 micrometers or 0.4 seconds of arc, a level which is not achievable through pre-flight metrology. We describe a technique for determining the CCD positioning using images of the Kepler field of view (FOV) obtained in flight. The technique uses the fitted centroid row and column positions of 400 pre-selected stars on each CCD to obtain empirical polynomials which relate sky coordinates (right ascension and declination) to chip coordinates (row and column). The polynomials are in turn evaluated to produce constraints for a nonlinear model fit which directly determines the model parameters describing the location and orientation of each CCD. The focal plane geometry characterization algorithm is itself embedded in an iterative process which determines the focal plane geometry and the Pixel Response Function for each CCD in a self-consistent manner. In addition to the fully automated calculation, a person-in-the-loop implementation was developed to allow an initial determination of the geometry in the event of large misalignments, achieving a much looser capture tolerance for more modest accuracy and reduced automation
Modeling human intuitions about liquid flow with particle-based simulation
Humans can easily describe, imagine, and, crucially, predict a wide variety
of behaviors of liquids--splashing, squirting, gushing, sloshing, soaking,
dripping, draining, trickling, pooling, and pouring--despite tremendous
variability in their material and dynamical properties. Here we propose and
test a computational model of how people perceive and predict these liquid
dynamics, based on coarse approximate simulations of fluids as collections of
interacting particles. Our model is analogous to a "game engine in the head",
drawing on techniques for interactive simulations (as in video games) that
optimize for efficiency and natural appearance rather than physical accuracy.
In two behavioral experiments, we found that the model accurately captured
people's predictions about how liquids flow among complex solid obstacles, and
was significantly better than two alternatives based on simple heuristics and
deep neural networks. Our model was also able to explain how people's
predictions varied as a function of the liquids' properties (e.g., viscosity
and stickiness). Together, the model and empirical results extend the recent
proposal that human physical scene understanding for the dynamics of rigid,
solid objects can be supported by approximate probabilistic simulation, to the
more complex and unexplored domain of fluid dynamics.Comment: Under review at PLOS Computational Biolog
Modeling human ad hoc coordination
Whether in groups of humans or groups of computer agents, collaboration is most effective between individuals who have the ability to coordinate on a joint strategy for collective action. However, in general a rational actor will only intend to coordinate if that actor believes the other group members have the same intention. This circular dependence makes rational coordination difficult in uncertain environments if communication between actors is unreliable and no prior agreements have been made. An important normative question with regard to coordination in these ad hoc settings is therefore how one can come to believe that other actors will coordinate, and with regard to systems involving humans, an important empirical question is how humans arrive at these expectations. We introduce an exact algorithm for computing the infinitely recursive hierarchy of graded beliefs required for rational coordination in uncertain environments, and we introduce a novel mechanism for multiagent coordination that uses it. Our algorithm is valid in any environment with a finite state space, and extensions to certain countably infinite state spaces are likely possible. We test our mechanism for multiagent coordination as a model for human decisions in a simple coordination game using existing experimental data. We then explore via simulations whether modeling humans in this way may improve human-Agent collaboration
A 3D Face Modelling Approach for Pose-Invariant Face Recognition in a Human-Robot Environment
Face analysis techniques have become a crucial component of human-machine
interaction in the fields of assistive and humanoid robotics. However, the
variations in head-pose that arise naturally in these environments are still a
great challenge. In this paper, we present a real-time capable 3D face
modelling framework for 2D in-the-wild images that is applicable for robotics.
The fitting of the 3D Morphable Model is based exclusively on automatically
detected landmarks. After fitting, the face can be corrected in pose and
transformed back to a frontal 2D representation that is more suitable for face
recognition. We conduct face recognition experiments with non-frontal images
from the MUCT database and uncontrolled, in the wild images from the PaSC
database, the most challenging face recognition database to date, showing an
improved performance. Finally, we present our SCITOS G5 robot system, which
incorporates our framework as a means of image pre-processing for face
analysis
The Kepler Pixel Response Function
Kepler seeks to detect sequences of transits of Earth-size exoplanets
orbiting Solar-like stars. Such transit signals are on the order of 100 ppm.
The high photometric precision demanded by Kepler requires detailed knowledge
of how the Kepler pixels respond to starlight during a nominal observation.
This information is provided by the Kepler pixel response function (PRF),
defined as the composite of Kepler's optical point spread function, integrated
spacecraft pointing jitter during a nominal cadence and other systematic
effects. To provide sub-pixel resolution, the PRF is represented as a
piecewise-continuous polynomial on a sub-pixel mesh. This continuous
representation allows the prediction of a star's flux value on any pixel given
the star's pixel position. The advantages and difficulties of this polynomial
representation are discussed, including characterization of spatial variation
in the PRF and the smoothing of discontinuities between sub-pixel polynomial
patches. On-orbit super-resolution measurements of the PRF across the Kepler
field of view are described. Two uses of the PRF are presented: the selection
of pixels for each star that maximizes the photometric signal to noise ratio
for that star, and PRF-fitted centroids which provide robust and accurate
stellar positions on the CCD, primarily used for attitude and plate scale
tracking. Good knowledge of the PRF has been a critical component for the
successful collection of high-precision photometry by Kepler.Comment: 10 pages, 5 figures, accepted by ApJ Letters. Version accepted for
publication
Reimagining the research-practice relationship: policy recommendations for informatics-enabled evidence-generation across the US health system
Abstract. The widespread adoption and use of electronic health records and their use to enable learning health systems
(LHS) holds great promise to accelerate both evidence-generating medicine (EGM) and evidence-based medicine (EBM), thereby enabling a LHS. In 2016, AMIA convened its 10th annual Policy Invitational to discuss issues
key to facilitating the EGM-EBM paradigm at points-of-care (nodes), across organizations (networks), and to ensure viability of this model at scale (sustainability). In this article, we synthesize discussions from the conference
and supplements those deliberations with relevant context to inform ongoing policy development. Specifically,
we explore and suggest public policies needed to facilitate EGM-EBM activities on a national scale, particularly
those policies that can enable and improve clinical and health services research at the point-of-care, accelerate
biomedical discovery, and facilitate translation of findings to improve the health of individuals and population
- …