Anytime Algorithm

See: Prediction Algorithm, Decision Task.

References

http://en.wikipedia.org/wiki/Anytime_algorithm
- In computer science an anytime algorithm is an algorithm that can return a valid solution to a problem even if it's interrupted at any time before it ends. The algorithm is expected to find better and better solutions the more time it keeps running.
  Most algorithms run to completion: they provide a single answer after performing some fixed amount of computation. In some cases, however, the user may wish to terminate the algorithm prior to completion. The amount of the computation required may be substantial, for example, and computational resources might need to be reallocated. Most algorithms either run to completion or they provide no useful solution information. Anytime algorithms, however, are able to return a partial answer, whose quality depends on the amount of computation they were able to perform. The answer generated by anytime algorithms is an approximation of the correct answer.

(Sammut & Webb, 2011) ⇒ Claude Sammut (editor), and Geoffrey I. Webb (editor). (2011). “Anytime Algorithm.” In: (Sammut & Webb, 2011) p.40

(Mott & Lester, 2006) ⇒ Bradford W. Mott, and James C. Lester. (2006). “U-director: A decision-theoretic narrative planning architecture for storytelling environments.” In: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems. doi:10.1145/1160633.1160808
- QUOTE: … Moreover, stochastic sampling methods typically have an “anytime” property which is particularly attractive for real-time applications.
(Ueno et al., 2006) ⇒ Ken Ueno, Xiaopeng Xi, Eamonn Keogh, and Dah-Jye Lee. (2006). “Anytime Classification Using the Nearest Neighbor Algorithm with Applications to Stream Mining.” In: Proceedings of the Sixth International Conference on Data Mining. doi:10.1109/ICDM.2006.21