NotesFAQContact Us
Search Tips
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ1115794
Record Type: Journal
Publication Date: 2013-Oct
Pages: 10
Abstractor: As Provided
ISSN: EISSN-1932-6246
Solving Large Problems with a Small Working Memory
Pizlo, Zygmunt; Stefanov, Emil
Journal of Problem Solving, v6 n1 Article 5 p34-43 Oct 2013
We describe an important elaboration of our multiscale/multiresolution model for solving the Traveling Salesman Problem (TSP). Our previous model emulated the non-uniform distribution of receptors on the human retina and the shifts of visual attention. This model produced near-optimal solutions of TSP in linear time by performing hierarchical clustering followed by a sequence of coarse-to-fine approximations of the tour. Linear time complexity was related to the minimal amount of search performed by the model, which posed minimal requirements on the size of the working memory. The new model implements the small working memory requirement. The model only stores information about as few as 2-5 clusters at any one time in the solution process. This requirement matches the known capacity of human working memory. We conclude by speculating that this model provides a possible explanation of how the human mind can effectively deal with very large search spaces.
Purdue University Press. Stewart Center Room 370, 504 West State Street, West Lafayette, IN 47907. Tel: 800-247-6553; Fax: 419-281-6883; e-mail: pupress@purdue,edu; Web site:
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A