Adversarial multi-robot problems, where teams of robots compete with one another, require the development of approaches that span all levels of control and integrate algorithms ra...
James Bruce, Michael H. Bowling, Brett Browning, M...
This work addresses the problem of efficiently learning action schemas using a bounded number of samples (interactions with the environment). We consider schemas in two languages-...
—Instantaneous detection and diagnosis of various faults and break-downs in industrial processes is required to reduce production losses and damage to equipments. A solved knowle...
The paper investigates the use of computational intelligence for adaptive lesson presentation in a Web-based learning environment. A specialized connectionist architecture is devel...
Kyparisia A. Papanikolaou, George D. Magoulas, Mar...
RVRL (Rule Value Reinforcement Learning) is a new algorithm which extends an existing learning framework that models the environment of a situated agent using a probabilistic rule...