The existing reinforcement learning methods have been seriously suffering from the curse of dimension problem especially when they are applied to multiagent dynamic environments. ...
While the ”‘quasi-state-of-the-art”’ towards acoustic emotion recognition relies on multivariate time-series analysis of e.g. pitch, energy, or MFCC by statistical functio...
Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...
The domain of robotic soccer is known as a highly dynamic and non-deterministic environment for multiagent research. We introduce an approach using Hierarchical Task Network planni...
Structured Hidden Markov Models (S-HMM) are a variant of Hierarchical Hidden Markov Models; it provides an abstraction mechanism allowing a high level symbolic description of the k...