MDPs are an attractive formalization for planning, but realistic problems often have intractably large state spaces. When we only need a partial policy to get from a fixed start s...
H. Brendan McMahan, Maxim Likhachev, Geoffrey J. G...
Abstract. This paper presents a methodology for automatically customizing a scenario to suit a learner’s abilities, needs, or goals. Training scenarios are often utilized to give...
Many verification, planning, and control problems can be modeled as games played on state-transition graphs by one or two players whose conflicting goals are to form a path in th...
Krishnendu Chatterjee, Marcin Jurdzinski, Thomas A...
We consider the problem of planning optimally in potentially concurrent probabilistic domains: actions have probabilistic effects and may execute in parallel under certain conditi...
We consider the problem of planning optimally in potentially concurrent probabilistic domains: actions have probabilistic effects and may execute in parallel under certain conditi...