We consider networks of workstations which are not only timesharing, but also heterogeneous with a large variation in the computing power and memory capacities of different workst...
Representing agent policies compactly is essential for improving the scalability of multi-agent planning algorithms. In this paper, we focus on developing a pruning technique that...
We present a framework that enables a belief-desire-intention (BDI) agent to dynamically choose its intention reconsideration policy in order to perform optimally in accordance wi...
Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
—The paper presents a novel integrated MAC/routing scheme for wireless sensor networking. Our design objective is to elect the next hop for data forwarding by minimizing the numb...