Sets of features in Markov decision processes can play a critical role in approximately representing value and in abstracting the state space. Selection of features is crucial to the success of a system and is most often conducted by a human. We study the problem of automatically selecting problem features, and propose and evaluate a simple approach reducing the problem of selecting a new featu...

Approximate reinforcement learning deals with the essential problem of applying reinforcement learning in large and continuous state-action spaces, by using function approximators to represent the solution. This chapter reviews least-squares methods for policy iteration, an important class of algorithms for approximate reinforcement learning. We discuss three techniques for solving the core, po...

For solving linear ill-posed problems, regularizationmethods are requiredwhen the right-hand side is with some noise. In this paper regularized solutions are obtained by implicit iteration methods in Hilbert scales. By exploiting operator monotonicity of certain functions and interpolation techniques in variable Hilbert scales, we study these methods under general smoothness conditions. Order o...

In this paper, the Kadomtsev-Petviashvili equation is solved by using the Adomian’s decomposition method , modified Adomian’s decomposition method , variational iteration method , modified variational iteration method, homotopy perturbation method, modified homotopy perturbation method and homotopy analysis method. The existence and uniqueness of the solution and convergence of the proposed...

In this paper, we present a full Newton step feasible interior-pointmethod for circular cone optimization by using Euclidean Jordanalgebra. The search direction is based on the Nesterov-Todd scalingscheme, and only full-Newton step is used at each iteration.Furthermore, we derive the iteration bound that coincides with thecurrently best known iteration bound for small-update methods.

ed knowledge Visual interface Visual communication Data Interaction Update Manage Learn Visualize Apply or update Apply or update Figure 1. The visual analytics process. The user seeks to create a formal model that captures the analytics problem’s underlying mechanisms. In an iterative learning process, the user continuously teaches the computer using his or her informal domain knowledge and ex...

in this paper, we consider convex quadratic semidefinite optimization problems and provide a primal-dual interior point method (ipm) based on a new kernel function with a trigonometric barrier term. iteration complexity of the algorithm is analyzed using some easy to check and mild conditions. although our proposed kernel function is neither a self-regular (sr) function nor logarithmic barrier ...

In this paper, we apply the local fractional Adomian decomposition and variational iteration methods to obtain the analytic approximate solutions of Fredholm integral equations of the second kind within local fractional derivative operators. The iteration procedure is based on local fractional derivative. The obtained results reveal that the proposed methods are very efficient and simple tools ...