Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
The distributed constraint satisfaction problem (CSP) is a general formalization used to represent problems in distributed multi-agent systems. To deal with realistic problems, mu...
Energy dissipation in cache memories is becoming a major design issue in embedded microprocessors. Predictive filter cache based instruction cache hierarchy is effective in reduci...
To enhance the widespread use of a parallel supply chain simulator, a web front-end that enables access at any time and from any location has been developed. The front-end provide...
Boon-Ping Gan, Li Liu, Zhengrong Ji, Stephen John ...
We present a novel framework for hierarchical collision detection that can be applied to virtually all bounding volume (BV) hierarchies. It allows an application to trade quality ...