Selecting the right algorithm (2001) [5 citations — 1 self]
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@INPROCEEDINGS{Lagoudakis01selectingthe,author = {Michail G. Lagoudakis and Michael L. Littman and Ronald E. Parr},
title = {Selecting the right algorithm},
booktitle = {In Proceedings of the 2001 AAAI Fall Symposium Series: Using Uncertainty within Computation},
year = {2001}
}
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Abstract:
Computer scientists always strive to find better and faster algorithms for any computational problem. It is usually true that programmers and/or users come across a plethora of different algorithms when looking to solve a particular problem efficiently. Each one of these algorithms might offer different guarantees and properties, but it is unlikely that a single one of them is the best (fastest) in all possible cases. So, the question that the programmer/user typically faces is: "Which algorithm should I select?" This question is largely due to the uncertainty in the input space, the inner workings of the algorithm (especially true for randomized algorithms), and the hardware characteristics. It's hard to know in advance what kind of inputs will be provided, how exactly the computation will proceed, or even how efficiently the underlying hardware will support
Citations
| 5824 | Introduction to Algorithms – Cormen, Leiserson, et al. - 1990 |
| 37 | Algorithm selection using reinforcement learning – Lagoudakis, Littman - 2000 |
| 14 | Learning to select branching rules in the DPLL procedure for satisfiability – Lagoudakis, Littman - 2001 |
