Originally designed as a component of the Belt and Road Initiative (BRI) under the pillar of people-to-people bonds, the Health Silk Road (HSR) has aroused intense interest and scrutiny amid the Covid-19 pandemic. Rather than a new geopolitical strategy within the BRI framework, the HSR is an emerging diplomatic initiative for promoting health cooperation in a world increasingly threatened by proliferating public health emergencies. China’s medical aid in the developing world before the HSR’s inception and broader health diplomacy since the onset of the coronavirus crisis have been misinterpreted in much of the developed world and some Asian neighbors. Although the HSR will be a bumpy road in a post-coronavirus era of growing geopolitical rivalry and fractured world market, the health cooperation initiative can still be built into a transregional health network to the benefit of nations concerned. To achieve this end, Beijing should take a two-pronged approach: building up a stronger and more resilient domestic health system and upgrading its multilayered partnerships with BRI participant nations and international organizations.

As China's Belt and Road Initiative (BRI) quickly evolves into an updated version for realizing high-quality development, its long-term success will increasingly depend on how well it can earn international legitimacy and credibility. Since sustainability is a critical source of credibility for the BRI, it is necessary to move the BRI forward by amplifying its role as a development agenda and tapping its potential to support global sustainable development and facilitate implementation of the United Nations' 2030 Agenda for Sustainable Development (2030 Agenda) through delivering more public goods to other developing countries. The BRI projects designed to strengthen infrastructure inter-connectivity can greatly fit the developmental needs of countries along the routes and expedite their achievement of sustainable development goals (SDGs), both explicitly and implicitly. Besides, the growing alignment between the BRI

In cooperative multi-agent reinforcement learning (CMARL), it is critical for agents to achieve a balance between self-exploration and team collaboration. However, agents can hardly accomplish the team task without coordination and they would be trapped in a local optimum where easy cooperation is accessed without enough individual exploration. Recent works mainly concentrate on agents' coordinated exploration, which brings about the exponentially grown exploration of the state space. To address this issue, we propose Self-Motivated Multi-Agent Exploration (SMMAE), which aims to achieve success in team tasks by adaptively finding a trade-off between self-exploration and team cooperation. In SM-MAE, we train an independent exploration policy for each agent to maximize their own visited state space. Each agent learns an adjustable exploration probability based on the stability of the joint team policy. The experiments on highly cooperative tasks in Star-Craft II micromanagement benchmark (SMAC) demonstrate that SMMAE can explore task-related states more efficiently, accomplish coordinated behaviours and boost the learning performance.

In cooperative multi-agent reinforcement learning (MARL), where agents only have access to partial observations, efficiently leveraging local information is critical. During long-time observations, agents can build awareness for teammates to alleviate the problem of partial observability. However, previous MARL methods usually neglect this kind of utilization of local information. To address this problem, we propose a novel framework, multi-agent Local INformation Decomposition for Awareness of teammates (LINDA), with which agents learn to decompose local information and build awareness for each teammate. We model the awareness as stochastic random variables and perform representation learning to ensure the informativeness of awareness representations by maximizing the mutual information between awareness and the actual trajectory of the corresponding agent. LINDA is agnostic to specific algorithms and can be flexibly integrated to different MARL methods. Sufficient experiments show that the proposed framework learns informative awareness from local partial observations for better collaboration and significantly improves the learning performance, especially on challenging tasks.

Based on the analytical framework of securitization, this article argues that cooperation between China and the United States on climate change will not lose momentum despite President Trump’s seemingly passive stance. A securitization process on the climate issue has been ongoing in China since President Xi Jinping took office and proposed the Overall National Security Outlook (ONSO). Climate security was thus integrated into China’s political discourse as a key component of ecological and common security, leading to a period of China-U.S. cooperation during the Obama administration. Similarly, in the United States, climate policy has been cemented in security planning and assessment of various federal agencies. The U.S. security sector seems to be largely unaffected by the White House decision to withdraw from the Paris Agreement. A growing number of Americans treat climate change as a security threat and many U.S. states and cities, in collaboration with business leaders, have taken on a role in international climate diplomacy. Combined with existing intergovernmental collaborative projects, robust market forces and innovative local initiatives will continue to push China-U.S. climate cooperation forward. As a necessary step to sustain its ties with the United States on climate issues, the Chinese government needs to propose a renewed bilateral framework on energy and environment cooperation under the China-U.S. Comprehensive Economic Dialogue.