In Reinforcement Learning (RL) there has been some experimental evidence that the residual gradient algorithm converges slower than the TD(0) algorithm. In this paper, we use the ...
In this paper, we show that the LVQ learning algorithm converges to locally asymptotic stable equilibria of an ordinary differential equation. We show that the learning algorithm ...
We show here how to construct a cellular automaton whose asymptotic set (the set of configurations it converges to) is maximally complex: it contains only configurations of maximal...
— Diversity–multiplexing tradeoff (DMT) presents a compact framework to compare various MIMO systems and channels in terms of the two main advantages they provide (i.e. high da...
We discuss a theory for a realistic, applicable scaled genetic algorithm (GA) which converges asymptoticly to global optima in a coevolutionary setting involving two species. It is...