# Decomposable Probability-of-Success Metrics in Algorithmic Search

### Tyler Sam, Jake Williams, Abel Tadesse, Huey Sun, George MontaÃ±ez

#### Abstract

Prior work in machine learning has used a specific success metric, the expected per-query probability of success, to prove impossibility results within the algorithmic search framework. However, this success metric prevents us from applying these results to specific subfields of machine learning, e.g. transfer learning. We define decomposable metrics as a category of success metrics for search problems which can be expressed as a linear operation on a probability distribution to solve this issue. Using an arbitrary decomposable metric to measure the success of a search, we demonstrate theorems which bound success in various ways, generalizing several existing results in the literature.

Download#### Paper Citation

#### in Harvard Style

Sam T., Williams J., Tadesse A., Sun H. and MontaÃ±ez G. (2020). **Decomposable Probability-of-Success Metrics in Algorithmic Search**.In *Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,* ISBN 978-989-758-395-7, pages 785-792. DOI: 10.5220/0009098807850792

#### in Bibtex Style

@conference{icaart20,

author={Tyler Sam and Jake Williams and Abel Tadesse and Huey Sun and George MontaÃ±ez},

title={Decomposable Probability-of-Success Metrics in Algorithmic Search},

booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},

year={2020},

pages={785-792},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0009098807850792},

isbn={978-989-758-395-7},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,

TI - Decomposable Probability-of-Success Metrics in Algorithmic Search

SN - 978-989-758-395-7

AU - Sam T.

AU - Williams J.

AU - Tadesse A.

AU - Sun H.

AU - MontaÃ±ez G.

PY - 2020

SP - 785

EP - 792

DO - 10.5220/0009098807850792