In interest point based human action recognition, local descriptors are used to represent information in the neighbourhood around each extracted space-time interest point. The per...
Progress in action recognition has been in large part due to advances in the features that drive learning-based methods. However, the relative sparsity of training data and the ri...
Reinforcement learning techniques are increasingly being used to solve di cult problems in control and combinatorial optimization with promising results. Implicit imitation can acc...
This paper presents the application of an action module planning method to an experimental climbing robot named LIBRA. The method searches for a sequence of physically realizable ...
Formal analyses of social action for Distributed A.I. (DAI) have focussed, almost exclusively, on scenarios in which participating agents have a joint intention to act. While such ...