Issue No. 01 - January (1988 vol. 37)

ISSN: 0018-9340

pp: 2-13

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/12.75146

ABSTRACT

Three deterministic learning automata solutions to the problem of equipartitioning are presented. Although the first two are epsilon -optimal, they seem to be practically feasible only when a set of W objects is small. The last solution, which uses a novel learning automaton, demonstrates an excellent partitioning capability. Experimentally, this solution converges an order of magnitude faster

INDEX TERMS

convergence rate; epsilon -optimal solutions; equipartitioning problem; deterministic learning automata solutions; deterministic automata; learning systems; set theory.

CITATION

D.C.Y. Ma, B.J. Oommen, "Deterministic Learning Automata Solutions to the Equipartitioning Problem",

*IEEE Transactions on Computers*, vol. 37, no. , pp. 2-13, January 1988, doi:10.1109/12.75146