2,923 research outputs found
Goal-Directed Planning for Habituated Agents by Active Inference Using a Variational Recurrent Neural Network
It is crucial to ask how agents can achieve goals by generating action plans
using only partial models of the world acquired through habituated
sensory-motor experiences. Although many existing robotics studies use a
forward model framework, there are generalization issues with high degrees of
freedom. The current study shows that the predictive coding (PC) and active
inference (AIF) frameworks, which employ a generative model, can develop better
generalization by learning a prior distribution in a low dimensional latent
state space representing probabilistic structures extracted from well
habituated sensory-motor trajectories. In our proposed model, learning is
carried out by inferring optimal latent variables as well as synaptic weights
for maximizing the evidence lower bound, while goal-directed planning is
accomplished by inferring latent variables for maximizing the estimated lower
bound. Our proposed model was evaluated with both simple and complex robotic
tasks in simulation, which demonstrated sufficient generalization in learning
with limited training data by setting an intermediate value for a
regularization coefficient. Furthermore, comparative simulation results show
that the proposed model outperforms a conventional forward model in
goal-directed planning, due to the learned prior confining the search of motor
plans within the range of habituated trajectories.Comment: 30 pages, 19 figure
Goal-Directed Behavior under Variational Predictive Coding: Dynamic Organization of Visual Attention and Working Memory
Mental simulation is a critical cognitive function for goal-directed behavior
because it is essential for assessing actions and their consequences. When a
self-generated or externally specified goal is given, a sequence of actions
that is most likely to attain that goal is selected among other candidates via
mental simulation. Therefore, better mental simulation leads to better
goal-directed action planning. However, developing a mental simulation model is
challenging because it requires knowledge of self and the environment. The
current paper studies how adequate goal-directed action plans of robots can be
mentally generated by dynamically organizing top-down visual attention and
visual working memory. For this purpose, we propose a neural network model
based on variational Bayes predictive coding, where goal-directed action
planning is formulated by Bayesian inference of latent intentional space. Our
experimental results showed that cognitively meaningful competencies, such as
autonomous top-down attention to the robot end effector (its hand) as well as
dynamic organization of occlusion-free visual working memory, emerged.
Furthermore, our analysis of comparative experiments indicated that
introduction of visual working memory and the inference mechanism using
variational Bayes predictive coding significantly improve the performance in
planning adequate goal-directed actions
Relative Generalized Rank Weight of Linear Codes and Its Applications to Network Coding
By extending the notion of minimum rank distance, this paper introduces two
new relative code parameters of a linear code C_1 of length n over a field
extension and its subcode C_2. One is called the relative
dimension/intersection profile (RDIP), and the other is called the relative
generalized rank weight (RGRW). We clarify their basic properties and the
relation between the RGRW and the minimum rank distance. As applications of the
RDIP and the RGRW, the security performance and the error correction capability
of secure network coding, guaranteed independently of the underlying network
code, are analyzed and clarified. We propose a construction of secure network
coding scheme, and analyze its security performance and error correction
capability as an example of applications of the RDIP and the RGRW. Silva and
Kschischang showed the existence of a secure network coding in which no part of
the secret message is revealed to the adversary even if any dim C_1-1 links are
wiretapped, which is guaranteed over any underlying network code. However, the
explicit construction of such a scheme remained an open problem. Our new
construction is just one instance of secure network coding that solves this
open problem.Comment: IEEEtran.cls, 25 pages, no figure, accepted for publication in IEEE
Transactions on Information Theor
New Parameters of Linear Codes Expressing Security Performance of Universal Secure Network Coding
The universal secure network coding presented by Silva et al. realizes secure
and reliable transmission of a secret message over any underlying network code,
by using maximum rank distance codes. Inspired by their result, this paper
considers the secure network coding based on arbitrary linear codes, and
investigates its security performance and error correction capability that are
guaranteed independently of the underlying network code. The security
performance and error correction capability are said to be universal when they
are independent of underlying network codes. This paper introduces new code
parameters, the relative dimension/intersection profile (RDIP) and the relative
generalized rank weight (RGRW) of linear codes. We reveal that the universal
security performance and universal error correction capability of secure
network coding are expressed in terms of the RDIP and RGRW of linear codes. The
security and error correction of existing schemes are also analyzed as
applications of the RDIP and RGRW.Comment: IEEEtran.cls, 8 pages, no figure. To appear in Proc. 50th Annual
Allerton Conference on Communication, Control, and Computing (Allerton 2012).
Version 2 added an exact expression of the universal error correction
capability in terms of the relative generalized rank weigh
Chiral spin-wave edge modes in dipolar magnetic thin films
Based on a linearized Landau-Lifshitz equation, we show that two-dimensional
periodic allay of ferromagnetic particles coupled with magnetic dipole-dipole
interactions supports chiral spin-wave edge modes, when subjected under the
magnetic field applied perpendicular to the plane. The mode propagates along a
one-dimensional boundary of the system in a unidirectional way and it always
has a chiral dispersion within a band gap for spin-wave volume modes. Contrary
to the well-known Damon-Eshbach surface mode, the sense of the rotation depends
not only on the direction of the field but also on the strength of the field;
its chiral direction is generally determined by the sum of the so-called Chern
integers defined for spin-wave volume modes below the band gap. Using simple
tight-binding descriptions, we explain how the magnetic dipolar interaction
endows spin-wave volume modes with non-zero Chern integers and how their values
will be changed by the field.Comment: 18 pages, 16 figures, some trivial typo in equations are fixe
Yang-Baxter deformations of Minkowski spacetime
We study Yang-Baxter deformations of 4D Minkowski spacetime. The Yang-Baxter
sigma model description was originally developed for principal chiral models
based on a modified classical Yang-Baxter equation. It has been extended to
coset curved spaces and models based on the usual classical Yang-Baxter
equation. On the other hand, for flat space, there is the obvious problem that
the standard bilinear form degenerates if we employ the familiar coset
Poincar\'e group/Lorentz group. Instead we consider a slice of AdS by
embedding the 4D Poincar\'e group into the 4D conformal group . With
this procedure we obtain metrics and -fields as Yang-Baxter deformations
which correspond to well-known configurations such as T-duals of Melvin
backgrounds, Hashimoto-Sethi and Spradlin-Takayanagi-Volovich backgrounds, the
T-dual of Grant space, pp-waves, and T-duals of dS and AdS. Finally we
consider a deformation with a classical -matrix of Drinfeld-Jimbo type and
explicitly derive the associated metric and -field which we conjecture to
correspond to a new integrable system.Comment: 27 pages, no figure, LaTe
Re-evaluation of waist circumference in metabolic syndrome: a comparison between Japanese men and women
We re-evaluated the criteria for waist circumference to predict the accumulation of the components of metabolic syndrome. We used data for 3,185 Japanese, aged 20-79 years. Metabolic syndrome has recently been redefined by a new criterion in Japan, in which waist circumference cutoff points, i.e. 85 cm for men and 90 cm for women, are employed. Among the 3,185 Japanese considered in the present study, 335 men (26.8%) and 69 women (3.6%) were diagnosed as having metabolic syndrome. A cutoff point as a predictor for 2 or more components of metabolic syndrome was evaluated by sensitivity/specificity and a receiver operating characteristic (ROC) curve. The optimal point was estimated as being approximately 85 cm of waist circumference in men and 75 cm in women. We therefore recommend a cutoff value, 75 cm of waist circumference, for the criterion of metabolic syndrome in women
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