In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
Design problems involve issues of stylistic preference and flexible standards of success; human designers often proceed by intuition and are unaware of following any strict rule-b...
We present a novel cognitive agent architecture and demonstrate its effectiveness in the Sense and Respond Logistics (SRL) domain. Effective applications to support SRL must antic...
Kshanti A. Greene, David G. Cooper, Anna L. Buczak...
We present a method for transforming the infinite interactive state space of interactive POMDPs (I-POMDPs) into a finite one, thereby enabling the computation of exact solutions. ...
Despite the success of the BDI approach to agent teamwork, initial role allocation (i.e. deciding which agents to allocate to key roles in the team) and role reallocation upon fai...