Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
We present a framework of cognitive network management by means of an autonomic reconfiguration scheme. We propose a network architecture that enables intelligent services to meet ...
Minsoo Lee, Dan Marconett, Xiaohui Ye, S. J. Ben Y...
This paper presents a multiagent architecture that facilitates active learning in educational environments for dependents. The multiagent architecture incorporates agents that can ...
er has outlined the potential of multiagent framework for decision support. From an abstract point of view, the concept of an agent has been used as modularization principle for th...
We introduce the ALeRT (Action-dependent Learning Rates with Trends) algorithm that makes two modifications to the learning rate and one change to the exploration rate of traditio...
Maria Cutumisu, Duane Szafron, Michael H. Bowling,...