Two of the most efficient planners for planning in nondeterministic domains are MBP and ND-SHOP2. MBP achieves its efficiency by using Binary Decision Diagrams (BDDs) to represent...
This paper discusses a design methodology of cooperative trajectory generation for multi-robot systems. The trajectory of achieving cooperative tasks, i.e., with temporal constrai...
Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
Hanna Kurniawati, Yanzhu Du, David Hsu, Wee Sun Le...
This paper addresses the problem of plan recognition for multiagent teams. Complex multi-agent tasks typically require dynamic teams where the team membership changes over time. T...
Task planning for mobile robots usually relies solely on spatial information and on shallow domain knowledge, like labels attached to objects and places. Although spatial informat...