Issue No. 01 - January (1988 vol. 37)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/12.75146
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
convergence rate; epsilon -optimal solutions; equipartitioning problem; deterministic learning automata solutions; deterministic automata; learning systems; set theory.
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