作者：HAN, SP; PANG, JS; RANGARAJ, N
作者单位：Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Bombay
摘要：This paper presents some globally convergent descent methods for solving systems of nonlinear equations defined by locally Lipschitzian functions. These methods resemble the well-known family of damped Newton and Gauss-Newton methods for solving systems of smooth equations; they generalize some recent Newton-like methods for solving B-differentiable equations which arise from various mathematical programs.
作者：SCHAL, M
摘要：For a semi-Markov decision model with average return, the validity of the second optimality equation is shown in the (nonmodified) form where the actions run through the set of all admissible actions rather than through the set of maximum points (conserving actions) for the first optimality equation. As a consequence the existence of a strongly optimal stationary policy is shown. The results seem to be known only for finite state finite action models whereas here countable state compact action...
