Multi-agent RL

Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates with Task Similarity

Multi-agent reinforcement learning (MARL) has primarily focused on solving a single task in isolation, while in practice the environment is often evolving, leaving many related tasks to be solved. In this paper, we investigate the benefits of …

SIMPPO: A Scalable and Incremental Online Learning Framework for Serverless Resource Management

Serverless Function-as-a-Service (FaaS) offers improved programmability for customers, yet it is not server-"less" and comes at the cost of more complex infrastructure management (e.g., resource provisioning and scheduling) for cloud providers. To …

A Mean-Field Game Approach to Cloud Resource Management with Function Approximation

Reinforcement learning (RL) has gained increasing popularity for resource management in cloud services such as serverless computing. As self-interested users compete for shared resources in a cluster, the multi-tenancy nature of serverless platforms …