Heuristic Speed-Ups for Learning in Complex Stochastic Environments
Christian J. Darken · 2005
We describe a novel mothodology by which a software agent can learn to predict future events in complex stochastic environments together with an important heuristic-based acceleration technique for computing the prediction. This speed-up enables us to use much more context in our predictions than was previously possible (Darken, 2005). We present results gathered from a first prototype of our approach.