1,407 research outputs found
On Two-Pair Two-Way Relay Channel with an Intermittently Available Relay
When multiple users share the same resource for physical layer cooperation
such as relay terminals in their vicinities, this shared resource may not be
always available for every user, and it is critical for transmitting terminals
to know whether other users have access to that common resource in order to
better utilize it. Failing to learn this critical piece of information may
cause severe issues in the design of such cooperative systems. In this paper,
we address this problem by investigating a two-pair two-way relay channel with
an intermittently available relay. In the model, each pair of users need to
exchange their messages within their own pair via the shared relay. The shared
relay, however, is only intermittently available for the users to access. The
accessing activities of different pairs of users are governed by independent
Bernoulli random processes. Our main contribution is the characterization of
the capacity region to within a bounded gap in a symmetric setting, for both
delayed and instantaneous state information at transmitters. An interesting
observation is that the bottleneck for information flow is the quality of state
information (delayed or instantaneous) available at the relay, not those at the
end users. To the best of our knowledge, our work is the first result regarding
how the shared intermittent relay should cooperate with multiple pairs of users
in such a two-way cooperative network.Comment: extended version of ISIT 2015 pape
Modeling of polyethylene, poly(l-lactide), and CNT composites: a dissipative particle dynamics study
Dissipative particle dynamics (DPD), a mesoscopic simulation approach, is used to investigate the effect of volume fraction of polyethylene (PE) and poly(l-lactide) (PLLA) on the structural property of the immiscible PE/PLLA/carbon nanotube in a system. In this work, the interaction parameter in DPD simulation, related to the Flory-Huggins interaction parameter χ, is estimated by the calculation of mixing energy for each pair of components in molecular dynamics simulation. Volume fraction and mixing methods clearly affect the equilibrated structure. Even if the volume fraction is different, micro-structures are similar when the equilibrated structures are different. Unlike the blend system, where no relationship exists between the micro-structure and the equilibrated structure, in the di-block copolymer system, the micro-structure and equilibrated structure have specific relationships
Diffusion Model-Augmented Behavioral Cloning
Imitation learning addresses the challenge of learning by observing an
expert's demonstrations without access to reward signals from environments.
Most existing imitation learning methods that do not require interacting with
environments either model the expert distribution as the conditional
probability p(a|s) (e.g., behavioral cloning, BC) or the joint probability p(s,
a) (e.g., implicit behavioral cloning). Despite its simplicity, modeling the
conditional probability with BC usually struggles with generalization. While
modeling the joint probability can lead to improved generalization performance,
the inference procedure can be time-consuming and it often suffers from
manifold overfitting. This work proposes an imitation learning framework that
benefits from modeling both the conditional and joint probability of the expert
distribution. Our proposed diffusion model-augmented behavioral cloning (DBC)
employs a diffusion model trained to model expert behaviors and learns a policy
to optimize both the BC loss (conditional) and our proposed diffusion model
loss (joint). DBC outperforms baselines in various continuous control tasks in
navigation, robot arm manipulation, dexterous manipulation, and locomotion. We
design additional experiments to verify the limitations of modeling either the
conditional probability or the joint probability of the expert distribution as
well as compare different generative models
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