Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
In many emerging applications, data streams are monitored in a network environment. Due to limited communication bandwidth and other resource constraints, a critical and practical...
While psychologists analyze network game-playing behavior in terms of players’ social interaction and experience, understanding user behavior is equally important to network res...
This editorial announces Algorithms for Molecular Biology, a new online open access journal published by BioMed Central. By launching the first open access journal on algorithmic ...
Query answers from on-line databases can easily be corrupted by hackers or malicious database publishers. Thus it is important to provide mechanisms which allow clients to trust th...
Charles U. Martel, Glen Nuckolls, Premkumar T. Dev...