Although several researchers have integrated methods for reinforcement learning (RL) with case-based reasoning (CBR) to model continuous action spaces, existing integrations typic...
In this paper, we study the spectrum assignment problem for wireless access networks. Opportunistic spectrum usage is a promising technology. However, it could suffer from the self...
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
We use game theorectic models to show the lack of incentives in the TCP congestion avoidance algorithm and the consequential systemwide network problems. We then propose a Vickery-...
Mixed-drove spatiotemporal co-occurrence patterns (MDCOPs) represent subsets of two or more different object-types whose instances are often located in spatial and temporal proximi...
Mete Celik, Shashi Shekhar, James P. Rogers, James...