Optimal and suboptimal decisions in perceptual problem-solving tasks

Abstract

Certain perceptual problem-solving tasks can be formulated as multistage decision-making problems. The dynamic programming approach can then be used to find the optimal decisions. When constraints are imposed on the problem-solver's ability to scan his environment and to process information, simple algorithms for solving the problem can be constructed. The algorithms yield suboptimal solutions that may adequately describe the problem-solver's behavior. Elithorn's perceptual maze test is reanalyzed and the results of an illustrative experiment are presented and discussed.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 3 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.