Scheduling of multiple parallel machinesin the face of sequence dependent setups and downstream considerations is a hard problem. No single efficient algorithm is guaranteedto pro...
Probabilistic planning algorithms seek e ective plans for large, stochastic domains. maxplan is a recently developed algorithm that converts a planning problem into an E-Majsat pr...
We present three systems for surface natural language generation that are trainable from annotated corpora. The first two systems, called NLG1 and NLG2, require a corpus marked on...
The degree to which a planner succeeds and meets response deadlines depends on the correctness and completenessof its modelswhichdescribe events and actions that change the world ...
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As s...
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koll...