✦ LIBER ✦

Module-Based Reinforcement Learning: Experiments with a Real Robot

✍ Scribed by Zsolt Kalmár; Csaba Szepesvári; András Lörincz

Book ID: 110250264
Publisher: Springer
Year: 1998
Tongue: English
Weight: 224 KB
Volume: 31
Category: Article
ISSN: 0885-6125
DOI: 10.1023/a:1007440607681

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Module-Based Reinforcement Learning: Exp

Module-Based Reinforcement Learning: Experiments with a Real Robot

✍ Zsolt Kalmár; Csaba Szepesvári; András Lőrincz 📂 Article 📅 1998 🏛 Springer US 🌐 English ⚖ 211 KB

Purposive Behavior Acquisition for a Rea

Purposive Behavior Acquisition for a Real Robot by Vision-Based Reinforcement Learning

✍ Asada, Minoru; Noda, Shoichi; Tawaratsumida, Sukoya; Hosoda, Koh 📂 Article 📅 1996 🏛 Springer 🌐 English ⚖ 449 KB

Acquisition of stand-up behavior by a re

Acquisition of stand-up behavior by a real robot using hierarchical reinforcement learning

✍ Jun Morimoto; Kenji Doya 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 564 KB

In this paper, we propose a hierarchical reinforcement learning architecture that realizes practical learning speed in real hardware control tasks. In order to enable learning in a practical number of trials, we introduce a low-dimensional representation of the state of the robot for higher-level pl

Reinforcement learning in a rule-based n

Reinforcement learning in a rule-based navigator for robotic manipulators

✍ Kaspar Althoefer; Bart Krekelberg; Dirk Husmeier; Lakmal Seneviratne 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 426 KB

Learning a DFT-based sequence with reinf

Learning a DFT-based sequence with reinforcement learning: a NAO implementation

✍ Boris Durán, Gauss Lee, Robert Lowe 📂 Article 📅 2012 🏛 SP Versita 🌐 English ⚖ 963 KB

Swarm robots reinforcement learning conv

Swarm robots reinforcement learning convergence accuracy-based learning classifier systems with gradient descent (XCS-GD)

✍ Shao, Jie; Lin, Haixia; Zhang, Kaibian 📂 Article 📅 2013 🏛 Springer-Verlag 🌐 English ⚖ 500 KB