Prominent achievements of multiagent reinforcement learning (MARL) have been recognized in the last few years, but effective cooperation among agents remains a challenge. Traditional methods neglect the modeling of action semantic relations in the learning process of joint action latent representations. In other words, the uncertain semantic relations might hinder the learning of sophisticated cooperative relationships among actions, which may lead to homogeneous behaviors across all agents and their limited exploration efficiency. Our aim is to learn the structure of the action semantic space to improve the cooperation‐aware representation for policy optimization of MARL. To achieve this, a scheme called graph learning of semantic relations (GLSR) is proposed, where action semantic embeddings and joint action representations are learned in a collaborative way. GLSR incorporates an action semantic encoder for capturing semantic relations in the action semantic space. By leveraging the cross‐attention mechanism with action semantic embeddings, GLSR prompts the action semantic relations to guide mining the cooperation‐aware joint action representations, implicitly facilitating agent cooperation in the joint policy space for more diverse behaviors of cooperative agents. The experimental results on challenging tasks demonstrate that GLSR attains state‐of‐the‐art outcomes and shows robust performance in multiagent cooperative tasks.

The MQTT protocol, a protocol based on the pub/sub (publish/subscribe) model, is widely used in the field of IoT. However, it poses certain security risks in areas such as data encryption, identity authentication, and access control. Smart healthcare is an important application domain of the IoT. With the increasing aging population, large amounts of sensitive information require data protection. To address this, we design a framework specifically tailored to ensure end-to-end (E2E) security in IoT communications within smart healthcare, and it does not require ensuring that the broker is in a trusted state; it can operate with a public broker service. This framework incorporates three key management systems, thereby fulfilling the smart healthcare’s requirements for secure and efficient communications and ensuring that data transmission throughout the entire solution is encrypted. Furthermore, in order to ensure that our scheme can be applied in real-life scenarios, we used common IoT hardware devices to validate the proposed framework. Experimental results demonstrate that our framework can satisfy the criteria for E2E communication security.

The restricted isometry property (RIP) is essential for the linear map to guarantee the successful recovery of low-rank matrices. The existing works show that the linear map generated by the measurement matrices with independent and identically distributed (i.i.d.) entries satisfies RIP with high probability. However, when dealing with non-i.i.d. measurement matrices, such as the rank-one measurements, the RIP compliance may not be guaranteed. In this paper, we show that the RIP can still be achieved with high probability, when the rank-one measurement matrix is constructed by the random unit-modulus vectors. Compared to the existing works, we first address the challenge of establishing RIP for the linear map in non-i.i.d. scenarios. As validated in the experiments, this linear map is memory-efficient, and not only satisfies the RIP but also exhibits similar recovery performance of the low-rank matrices to that of conventional i.i.d. measurement matrices.

Direct illumination rendering is an important technique in computer graphics. Precomputed radiance transfer algorithms can provide high quality rendering results in real time, but they can only support rigid models. On the other hand, ray tracing algorithms are flexible and can gracefully handle animated models. With NVIDIA RTX and the AI denoiser, we can use ray tracing algorithms to render visually appealing results in real time. Visually appealing though, they can deviate from the actual one considerably. We propose a visibility-boundary edge oriented infinite triangle bounding volume hierarchy (BVH) traversal algorithm to dynamically generate visibility in vector form. Our algorithm utilizes the properties of visibility-boundary edges and infinite triangle BVH traversal to maximize the efficiency of the vector form visibility generation. A novel data structure, temporal vectorized visibility, is proposed, which allows visibility in vector form to be shared across time and further increases the generation efficiency. Our algorithm can efficiently render close-to-reference direct illumination results. With the similar processing time, it provides a visual quality improvement around 10 dB in terms of peak signal-to-noise ratio (PSNR) w.r.t. the ray tracing algorithm reservoir-based spatiotemporal importance resampling (ReSTIR).

Deep neural networks boost many successful colorization methods, including automatic, interactive, and exemplar-based methods. Among them, interactive methods with global and/or local inputs are probably the most flexible to accurately add colors to a gray image. However, due to the sparseness of input-semantic correspondences, existing methods encounter difficulties in distributing inputs into correct regions. Moreover, they simply add or concatenate the features of different inputs to the network before color reconstruction, which cannot balance the influences of different inputs. To this end, we propose a novel interactive colorization network, which explicitly builds input-semantic correspondences with an attention mechanism and proposes a gated feature fusion module to balance the influences of global and local inputs. We further apply a differentiable histogram loss to impose a smooth impact of the global inputs. Extensive experiments demonstrate that our method can flexibly control the results and outperforms other state-of-the-art interactive methods.

A reconfigurable intelligent surface (RIS) allows a reflection transmission path between a base station (BS) and user equipment (UE). In wireless localization, this reflection path aids in positioning accuracy, especially when the line-of-sight (LOS) path is subject to severe blockage and fading. In this paper, we develop a RIS-aided positioning framework to locate a UE in environments where the LOS path may or may not be available. We first estimate the RIS-aided channel parameters from the received signals at the UE. To infer the UE position and clock bias from the estimated channel parameters, we propose a fusion method consisting of weighted least squares over the estimates of the LOS and reflection paths. We show that this approximates the maximum likelihood estimator under the large-sample regime and when the estimates from different paths are independent. We then optimize the RIS phase shifts to improve the positioning accuracy and extend the proposed approach to the case with multiple BSs and UEs. We derive Cramér-Rao bound (CRB) and demonstrate numerically that our proposed positioning method approaches the CRB.

Abstract Dual paraboloid mapping is an approach for environment mapping. Its major advantage is its fast map generation speed. For graphics applications, when filtering is needed, the filtering tool would naturally be mipmapping. However, directly applying mipmapping to dual paraboloid mapping would give us three problems. They are the discontinuity across the dual paraboloid map boundary, the non‐uniform sampling problem and the depth testing issue. We propose three approaches to solve these problems. Our approaches are based on some closed form equations derived via theoretical analysis. Using these equations, we modify the coordinates involved during the rendering process. In other words, these problems are handled just by using dual paraboloid maps and mipmaps differently, instead of fundamentally altering their data structures. Consequently, we are fixing the problems without damaging the map generation speed advantage. Applying all three approaches, we improve the rendering quality of dual paraboloid map mipmaps to a level equivalent to that of cubemap mipmaps, while preserving its fast map generation speed advantage. This gives dual paraboloid map mipmaps the potential to be a better choice than cubemap mipmaps for the devices with less computational power. The effectiveness and the efficiency of the proposed approaches are demonstrated using a glossy reflection application and an omnidirectional soft shadow generation application.