We present a new algorithm, called incremental least squares policy iteration (ILSPI), for finding the infinite-horizon stationary policy for partially observable Markov decision ...
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Abstract. A new iterative algorithm for the solution of minimization problems in infinitedimensional Hilbert spaces which involve sparsity constraints in form of p-penalties is pro...
Abstract. A reversible sequence of steps from the specification of the algorithm and the mathematical definition of the recurrent solution through the recursive procedure, the ta...
This paper presents a single-pass, view-dependent method to solve the rendering equation, using a stochastic iterational scheme where the transport operator is selected randomly i...