A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
The successful integration and acceptance of many multi-agent systems into daily lives crucially depends on the ability to develop effective policies for adjustable autonomy. Adju...
Rajiv T. Maheswaran, Milind Tambe, Pradeep Varakan...
In complex distributed applications, a problem is often decomposed into a set of subproblems that are distributed to multiple agents. We formulate this class of problems with a tw...
In many intelligence and security tasks it is necessary to monitor data in database in order to detect certain events or changes. Currently, database systems offer triggers to pro...
In this paper, we present our work on a level of detail(LoD) technique for human-like face models in virtual environments. Conventional LoD techniques have been adapted to allow f...