Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
We introduce a multi-label classification model and algorithm for labeling heterogeneous networks, where nodes belong to different types and different types have different sets of...
Ralitsa Angelova, Gjergji Kasneci, Fabian M. Sucha...
Reversible, or information-lossless, circuits have applications in digital signal processing, communication, computer graphics and cryptography. They are also a fundamental requir...
Vivek V. Shende, Aditya K. Prasad, Igor L. Markov,...
This paper presents a successful application of parallel (grid) coevolution applied to the building of an opening book (OB) in 9x9 Go. Known sayings around the game of Go are refou...
Pierre Audouard, Guillaume Chaslot, Jean-Baptiste ...
Abstract. Several schemes have been proposed for compactly representing multiattribute utility functions, yet none seems to achieve the level of success achieved by Bayesian and Ma...