Abstract— Real-world robotic environments are highly structured. The scalability of planning and reasoning methods to cope with complex problems in such environments crucially de...
Many problems used in AI planning including Blocks, Logistics, Gripper, Satellite, and others lack the interactions that characterize puzzles and can be solved nonoptimally in low...
We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
PDDL2.1 supports modelling of complex temporal planning domains in which solutions must exploit concurrency. Few existing temporal planners can solve problems that require concurr...
Amanda Jane Coles, Andrew Coles, Maria Fox, Derek ...
Wedescribe somenewpreprocessing techniques that enable faster domain-independentplanning. Thefirst set of techniquesis aimedat inferring state constraints from the structure of pl...