Sciweavers

8 search results - page 1 / 2
» Reinforcement Learning Hierarchical Neuro-Fuzzy Politree Mod...
Sort
View
HIS
2004
13 years 5 months ago
Reinforcement Learning Hierarchical Neuro-Fuzzy Politree Model for Control of Autonomous Agents
: This work presents a new hybrid neuro-fuzzy model for automatic learning of actions taken by agents. The main objective of this new model is to provide an agent with intelligence...
Karla Figueiredo, Marley B. R. Vellasco, Marco Aur...
ABIALS
2008
Springer
13 years 5 months ago
Multiscale Anticipatory Behavior by Hierarchical Reinforcement Learning
Abstract. In order to establish autonomous behavior for technical systems, the well known trade-off between reactive control and deliberative planning has to be considered. Within ...
Matthias Rungger, Hao Ding, Olaf Stursberg
ATAL
2010
Springer
13 years 4 months ago
Self-organization for coordinating decentralized reinforcement learning
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
AAAI
2010
13 years 5 months ago
The Model-Based Approach to Autonomous Behavior: A Personal View
The selection of the action to do next is one of the central problems faced by autonomous agents. In AI, three approaches have been used to address this problem: the programming-b...
Hector Geffner
JIRS
2000
144views more  JIRS 2000»
13 years 3 months ago
An Integrated Approach of Learning, Planning, and Execution
Agents (hardware or software) that act autonomously in an environment have to be able to integrate three basic behaviors: planning, execution, and learning. This integration is man...
Ramón García-Martínez, Daniel...