Abstract. On product domains, sparse-grid approximation yields optimal, dimension-independent convergence rates when the function that is approximated has L2-bounded mixed derivati...
A simultaneous perturbation stochastic approximation (SPSA) method has been developed in this paper, using the operators of perturbation with the Lipschitz density function. This ...
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
We prove two main results on how arbitrary linear threshold functions f(x) = sign(w · x − θ) over the n-dimensional Boolean hypercube can be approximated by simple threshold f...
CBR is one of the techniques that can be applied to the task of approximating a function over high-dimensional, continuous spaces. In Reinforcement Learning systems a learning agen...