Outputs (13)

Evaluation of Internal Models in Autonomous Learning (2018)
Journal Article
Smith, S. C., & Herrmann, J. M. (2019). Evaluation of Internal Models in Autonomous Learning. IEEE Transactions on Cognitive and Developmental Systems, 11(4), 463-472. https://doi.org/10.1109/tcds.2018.2865999

Internal models (IMs) can represent relations between sensors and actuators in natural and artificial agents. In autonomous robots, the adaptation of IMs and the adaptation of the behavior are interdependent processes which have been studied under pa... Read More about Evaluation of Internal Models in Autonomous Learning.

Homeokinetic Reinforcement Learning (2012)
Presentation / Conference Contribution
Smith, S. C., & Herrmann, J. M. (2012). Homeokinetic Reinforcement Learning. In F. Schwenker, & E. Trentin (Eds.), Partially Supervised Learning. PSL 2011 (82-91). https://doi.org/10.1007/978-3-642-28258-4_9

In order to find a control policy for an autonomous robot by reinforcement learning, the utility of a behaviour can be revealed locally through a modulation of the motor command by probing actions. For robots with many degrees of freedom, this type o... Read More about Homeokinetic Reinforcement Learning.

Clustering-Based Searching and Navigation in an Online News Source (2006)
Presentation / Conference Contribution
Smith, S. C., & Rodríguez, M. A. (2006, April). Clustering-Based Searching and Navigation in an Online News Source. Presented at 28th European Conference on IR Research, ECIR 2006, London, UK

The growing amount of online news posted on the WWW demands new algorithms that support topic detection, search, and navigation of news documents. This work presents an algorithm for topic detection that considers the temporal evolution of news and t... Read More about Clustering-Based Searching and Navigation in an Online News Source.