We combine three threads of research on approximate dynamic programming: sparse random sampling of states, value function and policy approximation using local models, and using lo...
In this paper, we present a theoretical analysis of the error with three basic Monte Carlo radiosity algorithms, based on continuous collision shooting random walks, discrete coll...
: Average case analysis forms an interesting and intriguing part of algorithm theory since it explains why some algorithms with bad worst-case complexity can better themselves in p...
Abstract Approximate simulation relations have recently been introduced as a powerful tool for the approximation of discrete and continuous systems. In this paper, we his abstracti...
Cognitive architectures need to resolve the diversity dilemma – i.e., to blend diversity and simplicity – in order to couple functionality and efficiency with integrability, e...