—Large-scale agent-based systems are required to self-optimize towards multiple, potentially conflicting, policies of varying spatial and temporal scope. As a result, not all ag...
Distributed W-Learning (DWL) is a reinforcement learningbased algorithm for multi-policy optimization in agent-based systems. In this poster we propose the use of DWL for decentra...
Resource allocation is a key problem in autonomic computing. In this paper we use a data center scenario to motivate the need for decentralization and cooperative negotiation, and...
Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart,...
In this paper we use a reinforcement learning algorithm with the aim to increase the autonomous lifetime of a Wireless Sensor Network (WSN) and decrease latency in a decentralized...