scholarly journals A review of current defeasible reasoning implementations

2008 ◽  
Vol 23 (3) ◽  
pp. 227-260 ◽  
Author(s):  
DANIEL BRYANT ◽  
PAUL KRAUSE
Keyword(s):  
Computational Complexity ◽  
Complexity Analysis ◽  
State Of The Art ◽  
Research Area ◽  
Formal Models ◽  
Important Goal ◽  
Future Directions ◽  
Current State ◽  
Practical Argumentation ◽  
Reasoning Engine

AbstractThis article surveys existing practical implementations of both defeasible and argumentation-based reasoning engines and associated literature. We aim to summarize the current state of the art in the research area, show that there are many similiarities and connections between the various implementations and also highlight the differences regarding evaluation goals and strategies. An important goal of this paper is to argue for the need for well-designed empirical evaluations, as well as formal complexity analysis, in order to justify the practical applicability of a reasoning engine. There are indeed many challenges to be faced in developing implementations of argumentation. Not least of these is the inherent computational complexity of the formal models. We cover some of the ways these challenges have been addressed, and provide pointers for future directions in realizing the goal of practical argumentation.

scholarly journals Multiple particle filtering for tracking wireless agents via Monte Carlo likelihood approximation

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Stephan Schlupkothen ◽  
Gerd Ascheid
Keyword(s):  
Monte Carlo ◽  
Computational Complexity ◽  
Particle Filtering ◽  
Gaussian Approximation ◽  
State Of The Art ◽  
Approximation Techniques ◽  
Accurate Localization ◽  
Likelihood Approximation ◽  
Current State ◽  
Multiple Particle

Abstract The localization of multiple wireless agents via, for example, distance and/or bearing measurements is challenging, particularly if relying on beacon-to-agent measurements alone is insufficient to guarantee accurate localization. In these cases, agent-to-agent measurements also need to be considered to improve the localization quality. In the context of particle filtering, the computational complexity of tracking many wireless agents is high when relying on conventional schemes. This is because in such schemes, all agents’ states are estimated simultaneously using a single filter. To overcome this problem, the concept of multiple particle filtering (MPF), in which an individual filter is used for each agent, has been proposed in the literature. However, due to the necessity of considering agent-to-agent measurements, additional effort is required to derive information on each individual filter from the available likelihoods. This is necessary because the distance and bearing measurements naturally depend on the states of two agents, which, in MPF, are estimated by two separate filters. Because the required likelihood cannot be analytically derived in general, an approximation is needed. To this end, this work extends current state-of-the-art likelihood approximation techniques based on Gaussian approximation under the assumption that the number of agents to be tracked is fixed and known. Moreover, a novel likelihood approximation method is proposed that enables efficient and accurate tracking. The simulations show that the proposed method achieves up to 22% higher accuracy with the same computational complexity as that of existing methods. Thus, efficient and accurate tracking of wireless agents is achieved.

scholarly journals Numerical methods for kinetic equations

Acta Numerica ◽  
2014 ◽  
Vol 23 ◽  
pp. 369-520 ◽  
Author(s):  
G. Dimarco ◽  
L. Pareschi
Keyword(s):  
Computational Complexity ◽  
Numerical Methods ◽  
State Of The Art ◽  
Kinetic Equations ◽  
Numerical Techniques ◽  
Asymptotic Preserving ◽  
Hybrid Schemes ◽  
Velocity Models ◽  
Current State ◽  
Number Of Particles

In this survey we consider the development and mathematical analysis of numerical methods for kinetic partial differential equations. Kinetic equations represent a way of describing the time evolution of a system consisting of a large number of particles. Due to the high number of dimensions and their intrinsic physical properties, the construction of numerical methods represents a challenge and requires a careful balance between accuracy and computational complexity. Here we review the basic numerical techniques for dealing with such equations, including the case of semi-Lagrangian methods, discrete-velocity models and spectral methods. In addition we give an overview of the current state of the art of numerical methods for kinetic equations. This covers the derivation of fast algorithms, the notion of asymptotic-preserving methods and the construction of hybrid schemes.

scholarly journals Immunoconjugates and long circulating systems: Origins, current state of the art and future directions

2013 ◽  
Vol 65 (1) ◽  
pp. 24-35 ◽  
Author(s):  
Alexander Koshkaryev ◽  
Rupa Sawant ◽  
Madhura Deshpande ◽  
Vladimir Torchilin
Keyword(s):  
State Of The Art ◽  
Future Directions ◽  
Current State

scholarly journals A Guideline for Effectively Synthesizing and Characterizing Magnetic Nanoparticles for Advancing Nanobiotechnology: A Review

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2554 ◽  
Author(s):  
Mohammad Reza Zamani Kouhpanji ◽  
Bethanie J. H. Stadler
Keyword(s):  
Magnetic Nanoparticles ◽  
Biomedical Applications ◽  
State Of The Art ◽  
Future Directions ◽  
Current State ◽  
Pros And Cons ◽  
Synthesis Routes ◽  
Size And Morphology ◽  
Excellent Source ◽  
Source Of Information

The remarkable multimodal functionalities of magnetic nanoparticles, conferred by their size and morphology, are very important in resolving challenges slowing the progression of nanobiotechnology. The rapid and revolutionary expansion of magnetic nanoparticles in nanobiotechnology, especially in nanomedicine and therapeutics, demands an overview of the current state of the art for synthesizing and characterizing magnetic nanoparticles. In this review, we explain the synthesis routes for tailoring the size, morphology, composition, and magnetic properties of the magnetic nanoparticles. The pros and cons of the most popularly used characterization techniques for determining the aforementioned parameters, with particular focus on nanomedicine and biosensing applications, are discussed. Moreover, we provide numerous biomedical applications and highlight their challenges and requirements that must be met using the magnetic nanoparticles to achieve the most effective outcomes. Finally, we conclude this review by providing an insight towards resolving the persisting challenges and the future directions. This review should be an excellent source of information for beginners in this field who are looking for a groundbreaking start but they have been overwhelmed by the volume of literature.

Interventional biliary radiology: current state-of-the-art and future directions

2013 ◽  
Vol 5 (6) ◽  
pp. 525-538 ◽  
Author(s):  
Andrew Shawyer ◽  
Mark D Goodwin ◽  
Robert N Gibson
Keyword(s):  
State Of The Art ◽  
Future Directions ◽  
Current State

Future Directions in Cognitive Engineering and Naturalistic Decision Making

1995 ◽  
Vol 39 (9) ◽  
pp. 450-453 ◽  
Author(s):  
Mica R. Endsley ◽  
Gary Klein ◽  
David D. Woods ◽  
Philip J. Smith ◽  
Stephen J. Selcon
Keyword(s):  
Decision Making ◽  
State Of The Art ◽  
Cognitive Engineering ◽  
Training Process ◽  
Naturalistic Decision Making ◽  
Future Directions ◽  
Current State ◽  
Near Future ◽  
And Training ◽  
Research Domain

Cognitive Engineering and Naturalistic Decision Making are presented as two related fields of endeavor that seek to understand how people process information and perform within complex systems and to develop ways of applying this knowledge within the design and training process This panel presents an overview of the current state of the art in this research domain and charts paths for needed developments in the field in the near future.

scholarly journals Autonomous Inspection of Geologic Repositories: Current State of the Art and Future Directions

2020 ◽  
Author(s):  
Yu Hsuan Lee ◽  
Ravi Kumar ◽  
Jacob Benz ◽  
HaliAnne McGee-Hilbert ◽  
Geoffrey Hollinger ◽  
...  
Keyword(s):  
State Of The Art ◽  
Future Directions ◽  
Current State ◽  
Autonomous Inspection
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