Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Though appropriate for core Internet infrastructure, the Internet Protocol is unsuited to routing within and between emerging ad-hoc edge networks due to its dependence on hierarc...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
Current methods for recognition and interpretation of architectural drawings are limited to either low-level analysis of paper drawings or interpretation of electronic drawings th...