114,484 research outputs found
Robust Kalman tracking and smoothing with propagating and non-propagating outliers
A common situation in filtering where classical Kalman filtering does not
perform particularly well is tracking in the presence of propagating outliers.
This calls for robustness understood in a distributional sense, i.e.; we
enlarge the distribution assumptions made in the ideal model by suitable
neighborhoods. Based on optimality results for distributional-robust Kalman
filtering from Ruckdeschel[01,10], we propose new robust recursive filters and
smoothers designed for this purpose as well as specialized versions for
non-propagating outliers. We apply these procedures in the context of a GPS
problem arising in the car industry. To better understand these filters, we
study their behavior at stylized outlier patterns (for which they are not
designed) and compare them to other approaches for the tracking problem.
Finally, in a simulation study we discuss efficiency of our procedures in
comparison to competitors.Comment: 27 pages, 12 figures, 2 table
Conformance Testing as Falsification for Cyber-Physical Systems
In Model-Based Design of Cyber-Physical Systems (CPS), it is often desirable
to develop several models of varying fidelity. Models of different fidelity
levels can enable mathematical analysis of the model, control synthesis, faster
simulation etc. Furthermore, when (automatically or manually) transitioning
from a model to its implementation on an actual computational platform, then
again two different versions of the same system are being developed. In all
previous cases, it is necessary to define a rigorous notion of conformance
between different models and between models and their implementations. This
paper argues that conformance should be a measure of distance between systems.
Albeit a range of theoretical distance notions exists, a way to compute such
distances for industrial size systems and models has not been proposed yet.
This paper addresses exactly this problem. A universal notion of conformance as
closeness between systems is rigorously defined, and evidence is presented that
this implies a number of other application-dependent conformance notions. An
algorithm for detecting that two systems are not conformant is then proposed,
which uses existing proven tools. A method is also proposed to measure the
degree of conformance between two systems. The results are demonstrated on a
range of models
Automatic Curriculum Learning For Deep RL: A Short Survey
Automatic Curriculum Learning (ACL) has become a cornerstone of recent
successes in Deep Reinforcement Learning (DRL).These methods shape the learning
trajectories of agents by challenging them with tasks adapted to their
capacities. In recent years, they have been used to improve sample efficiency
and asymptotic performance, to organize exploration, to encourage
generalization or to solve sparse reward problems, among others. The ambition
of this work is dual: 1) to present a compact and accessible introduction to
the Automatic Curriculum Learning literature and 2) to draw a bigger picture of
the current state of the art in ACL to encourage the cross-breeding of existing
concepts and the emergence of new ideas.Comment: Accepted at IJCAI202
Sufficient Conditions for Feasibility and Optimality of Real-Time Optimization Schemes - II. Implementation Issues
The idea of iterative process optimization based on collected output
measurements, or "real-time optimization" (RTO), has gained much prominence in
recent decades, with many RTO algorithms being proposed, researched, and
developed. While the essential goal of these schemes is to drive the process to
its true optimal conditions without violating any safety-critical, or "hard",
constraints, no generalized, unified approach for guaranteeing this behavior
exists. In this two-part paper, we propose an implementable set of conditions
that can enforce these properties for any RTO algorithm. This second part
examines the practical side of the sufficient conditions for feasibility and
optimality (SCFO) proposed in the first and focuses on how they may be enforced
in real application, where much of the knowledge required for the conceptual
SCFO is unavailable. Methods for improving convergence speed are also
considered.Comment: 56 pages, 15 figure
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