This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
We present a systematic way to generate (1) languages of (generalised) regular expressions, and (2) sound and complete axiomatizations thereof, for a wide variety of quantitative ...
Alexandra Silva, Filippo Bonchi, Marcello M. Bonsa...
— A systematic approach to solve seemingly nonconvex resource allocation problems in wireless cellular networks is studied in this paper. By revealing and exploiting the hidden c...
In order for an autonomous agent to behave robustly in a variety of environments, it must have the ability to learn approximations to many different functions. The function approx...
Large-scale distributed systems are hard to deploy, and distributed hash tables (DHTs) are no exception. To lower the barriers facing DHT-based applications, we have created a pub...
Sean C. Rhea, Brighten Godfrey, Brad Karp, John Ku...