Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...
is a unifying abstraction that simplifies data management by encapsulating different physical representations of the same logical data. Similar to a quBit (quantum bit), the parti...
Kaushik Veeraraghavan, Jason Flinn, Edmund B. Nigh...
Agent competition and coordination are two classical and most important tasks in multiagent systems. In recent years, there was a number of learning algorithms proposed to resolve ...
In a peer-to-peer file-sharing system, a client desiring a particular file must choose a source from which to download. The problem of selecting a good data source is difficult...
Daniel S. Bernstein, Zhengzhu Feng, Brian Neil Lev...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...