The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
In moving object databases, existing disk-based indexes are unable to keep up with the high update rate while providing speedy retrieval at the same time. However, efficient manage...
Optimal behavior is a very desirable property of autonomous agents and, as such, has received much attention over the years. However, making optimal decisions and executing optima...
Dynamic programming, branch-and-bound, and constraint programming are the standard solution principles for nding optimal solutions to machine scheduling problems. We propose a new ...
This paper extends the framework of partially observable Markov decision processes (POMDPs) to multi-agent settings by incorporating the notion of agent models into the state spac...