Name
Title | ||
|---|---|---|
Hierarchical neuro-fuzzy models based on reinforcement learning for intelligent agents |
Abstract | ||
|---|---|---|
This work introduces two new neuro-fuzzy systems for intelligent agents called Reinforcement Learning – Hierarchical Neuro-Fuzzy Systems BSP (RL-HNFB) and Reinforcement Learning – Hierarchical Neuro-Fuzzy Systems Politree (RL-HNFP). By using hierarchical partitioning methods, together with the Reinforcement Learning (RL) methodology, a new class of Neuro-Fuzzy Systems (SNF) was obtained, which executes, in addition to automatically learning its structure, the autonomous learning of the actions to be taken by an agent. These characteristics have been developed in order to bypass the traditional drawbacks of neuro-fuzzy systems. The paper details the two novel RL_HNF systems and evaluates their performance in a benchmark application – the cart-centering problem. The results obtained demonstrate the capacity of the proposed models in extracting knowledge from the agent's direct interaction with large and/or continuous environments. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11494669_52 | IWANN |
Keywords | Field | DocType |
autonomous learning,benchmark application,new neuro-fuzzy system,intelligent agent,new class,neuro-fuzzy systems,hierarchical neuro-fuzzy systems politree,reinforcement learning,hierarchical neuro-fuzzy model,neuro-fuzzy system,hierarchical neuro-fuzzy systems bsp,neuro fuzzy | Hierarchical control system,Neuro-fuzzy,Intelligent agent,Computer science,Unsupervised learning,Knowledge engineering,Artificial intelligence,Artificial neural network,Machine learning,Reinforcement learning,Learning classifier system | Conference |
Volume | ISSN | ISBN |
3512 | 0302-9743 | 3-540-26208-3 |
Citations | PageRank | References |
5 | 0.43 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Karla Figueiredo | 1 | 30 | 6.53 |
| Marley B. R. Vellasco | 2 | 280 | 47.47 |
| Marco Aurélio Pacheco | 3 | 77 | 11.36 |