The current evaluation functions for heuristic planning are expensive to compute. In numerous domains these functions give good guidance on the solution, so it worths the computat...
In the planning-as-SAT paradigm there have been numerous recent developments towards improving the speed and scalability of planning at the cost of finding a step-optimal parallel...
Nathan Robinson, Charles Gretton, Duc Nghia Pham, ...
The development of intelligent assistants has largely benefited from the adoption of decision-theoretic (DT) approaches that enable an agent to reason and account for the uncertai...
Bowen Hui, Sean Gustafson, Pourang Irani, Craig Bo...
One of the central problems in building broad-coverage story understanding systems is generating expectations about event sequences, i.e. predicting what happens next given some a...
In machine learning, decision trees are employed extensively in solving classification problems. In order to design a decision tree classifier two main phases are employed. The fi...
Jason R. Beck, Maria Garcia, Mingyu Zhong, Michael...