By Topic

Solving search problems with subgoals using an artificial neural network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ping Liang ; Coll. of Eng., California Univ., Riverside, CA, USA ; Jin, K.

Search problems with a series of subgoals can be solved using symbolic search algorithms. A method is proposed to use a neural network to perform this type of search by translating the serial and temporal resolution path into a spatial and parallel constraint structure using both state units and constraint units. A network is designed for the Missionaries and Cannibals Problem to illustrate the method. It is proved that every stable state of the neural network is definitely a feasible solution to the problem. The network finds the solution using a parallel stochastic relaxation algorithm. Computer simulation results are presented

Published in:

Neural Networks, 1993., IEEE International Conference on

Date of Conference:

1993