To provide real-time service or engineer constrained-based paths, networks require the underlying routing algorithm to be able to find low-cost paths that satisfy given Quality-of...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Abstract. Ant Colony Optimization (ACO) is a paradigm that employs a set of cooperating agents to solve functions or obtain good solutions for combinatorial optimization problems. ...
Streamlining communication is key to achieving good performance in shared-memory parallel programs. While full hardware support for cache coherence generally offers the best perfo...
Imagine some program and a number of changes. If none of these changes is applied (“yesterday”), the program works. If all changes are applied (“today”), the program does n...