We address a class of problems where decisions have to be optimized over a time horizon given that the future is uncertain and that the optimization decisions influence the time o...
In this paper, we propose the localized adaptive QoS routing scheme using POMDP(partially observable Markov Decision Processes) and Exploration Bonus. In order to deal with POMDP p...
Agents or agent teams deployed to assist humans often face the challenges of monitoring the state of key processes in their environment (including the state of their human users t...
Pradeep Varakantham, Rajiv T. Maheswaran, Milind T...
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP i...
Multi-agent reinforcement learning (MARL) is an emerging area of research. However, it lacks two important elements: a coherent view on MARL, and a well-defined problem objective. ...