An Analysis of Multi-Agent Reinforcement Learning for Decentralized Inventory Control Systems

Most solutions to the inventory management problem assume a centralization of information that is incompatible with organisational constraints in real supply chain networks. The inventory management problem is a well-known planning problem in operations research, concerned with finding the optimal re-order policy for nodes in a supply chain. While many centralized solutions to the problem exist, they are not applicable to real-world supply chains made up of independent entities. The problem can however be naturally decomposed into sub-problems, each associated with an independent entity, turning it into a multi-agent system. Therefore, a decentralized data-driven solution to inventory management problems using multi-agent reinforcement learning is proposed where each entity is controlled by an agent. Three multi-agent variations of the proximal policy optimization algorithm are investigated through simulations of different supply chain networks and levels of uncertainty. The centralized training decentralized execution framework is deployed, which relies on offline centralization during simulation-based policy identification, but enables decentralization when the policies are deployed online to the real system. Results show that using multi-agent proximal policy optimization with a centralized critic leads to performance very close to that of a centralized data-driven solution and outperforms a distributed model-based solution in most cases while respecting the information constraints of the system

National Cancer Institute Collaborative Workshop on Shaping the Landscape of Brain Metastases Research: challenges and recommended priorities

Brain metastases are an increasing global public health concern, even as survival rates improve for patients with metastatic disease. Both metastases and the sequelae of their treatment are key determinants of the inter-related priorities of patient survival, function, and quality of life, mandating a multidimensional approach to clinical care and research. At a virtual National Cancer Institute Workshop in September, 2022, key stakeholders convened to define research priorities to address the crucial areas of unmet need for patients with brain metastases to achieve meaningful advances in patient outcomes. This Policy Review outlines existing knowledge gaps, collaborative opportunities, and specific recommendations regarding consensus priorities and future directions in brain metastases research. Achieving major advances in research will require enhanced coordination between the ongoing efforts of individual organisations and consortia. Importantly, the continual and active engagement of patients and patient advocates will be necessary to ensure that the directionality of all efforts reflects what is most meaningful in the context of patient care