Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Abstract. Several challenges remain in the effort to build software capable of conducting realtime dialogue with people. Part of the problem has been a lack of realtime flexibili...
Ad-hoc Grids are highly heterogeneous and dynamic networks, one of the main challenges of resource allocation in such environments is to find mechanisms which do not rely on the ...
—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...
We describe an application of machine learning to the problem of geomorphic mapping of planetary surfaces. Mapping landforms on planetary surfaces is an important task and the fi...
Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta