Traditionally, there have been two large obstacles faced in attempting to apply AI techniques to games and other virtual environments. The first obstacle is the gap between the la...
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...
— In this paper, we propose a path planning method for nonholonomic multi-vehicle system in presence of moving obstacles. The objective is to find multiple fixed length paths f...
Ali Ahmadzadeh, Nader Motee, Ali Jadbabaie, George...
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
This paper presents a distributed planning and control architecture for autonomous Multi-Manipulator Systems (MMS). The control architecture is implemented using an agent-based ap...
Juan C. Fraile, Christiaan J. J. Paredis, Pradeep ...