Stochastic tasks: difficulty and Levin search

We establish a setting for asynchronous stochastic tasks that account for episodes, rewards and responses, and, most especially, the computational complexity of the algorithm behind an agent solving a task. This is used to determine the difficulty of a task as the (logarithm of the) number of computational steps required to acquire an acceptable policy for the task, which includes the exploration of policies and their verification. We also analyse instance difficulty, task compositions and decompositions.This work has been partially supported by the EU (FEDER) and the Spanish MINECO under grants TIN 2010-21062-C02-02, PCIN-2013-037 and TIN 2013-45732-C4-1-P, and by Generalitat Valenciana PROMETEOII 2015/013.Hernández Orallo, J. (2015). Stochastic tasks: difficulty and Levin search. En Artificial General Intelligence. Springer International Publishing. 90-100. http://hdl.handle.net/10251/66686S9010