Value prediction exploits localities in value streams. Previous research focused on exploiting two types of value localities, computational and context-based, in the local value h...
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
: Numerical function approximation over a Boolean domain is a classical problem with wide application to data modeling tasks and various forms of learning. A great many function ap...
This paper presents a hybrid compaction scheme for test responses containing unknown values, which consists of a space compactor and an unknown-blocking Multiple Input Signature R...
We identify two fundamental points of utilizing CBR for an adaptive agent that tries to learn on the basis of trial and error without a model of its environment. The first link co...