English

Ideal Partition of Resources for Metareasoning

Artificial Intelligence 2021-10-20 v1

Abstract

We can achieve significant gains in the value of computation by metareasoning about the nature or extent of base-level problem solving before executing a solution. However, resources that are irrevocably committed to metareasoning are not available for executing a solution. Thus, it is important to determine the portion of resources we wish to apply to metareasoning and control versus to the execution of a solution plan. Recent research on rational agency has highlighted the importance of limiting the consumption of resources by metareasoning machinery. We shall introduce the metareasoning-partition problem--the problem of ideally apportioning costly reasoning resources to planning a solution versus applying resource to executing a solution to a problem. We exercise prototypical metareasoning-partition models to probe the relationships between time allocated to metareasoning and to execution for different problem classes. Finally, we examine the value of metareasoning in the context of our functional analyses.

Keywords

Cite

@article{arxiv.2110.09624,
  title  = {Ideal Partition of Resources for Metareasoning},
  author = {Eric Horvitz and John Breese},
  journal= {arXiv preprint arXiv:2110.09624},
  year   = {2021}
}

Comments

12 pages, 5 figures. January 1990 technical report on principles of metareasoning and bounded optimality