Multi-agent problem domains may require distributed algorithms for a variety of reasons: local sensors, limitations of communication, and availability of distributed computational...
Sean Luke, Keith Sullivan, Liviu Panait, Gabriel C...
The existing reinforcement learning approaches have been suffering from the policy alternation of others in multiagent dynamic environments such as RoboCup competitions since othe...
In this paper, we propose a cautious cooperative learning approach using distributed case-based reasoning. Our approach consists of two learning mechanisms: individual and coopera...
In a navigation-oriented interaction paradigm, such as desktop, mixed and augmented virtual reality, recognizing the user needs is a valuable improvement, provided that the system...
We present a new method for blind document bleed through removal based on separate Markov Random Field (MRF) regularization for the recto and for the verso side, where separate pri...