We give the first complete theoretical convergence analysis for the iterative extensions of the Sturm/Triggs algorithm. We show that the simplest extension, SIESTA, converges to no...
We consider iterative algorithms of the form z := f(z), executed by a parallel or distributed computing system. We focus on asynchronous implementations whereby each processor ite...
Co-learning is a model involving agents from a large population, who interact by playing a fixed game and update their behaviour based on previous experience and the outcome of th...
Martin E. Dyer, Leslie Ann Goldberg, Catherine S. ...
We consider a finite-state Markov decision problem and establish the convergence of a special case of optimistic policy iteration that involves Monte Carlo estimation of Q-values,...
In iterative learning control schemes for linear discrete time systems, conditions to guarantee the monotonic convergence of the tracking9 error norms are derived. By using the Ma...