Efficient Constrained Portfolio Allocation using Simplex Decomposition in Reinforcement Learning

A novel approach to handle allocation constraints in portfolio optimization tasks by decomposing the constrained action space into a set of unconstrained allocation problems, outperforming state-of-the-art constrained reinforcement learning methods.