Learning in embedded systems / (Record no. 73126)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 03336nam a2200517 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 6267472 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220712204715.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 151224s2008 maua ob 001 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780262288507 |
| -- | electronic |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | |
| 082 00 - CLASSIFICATION NUMBER | |
| Call Number | 005.1 |
| 100 1# - AUTHOR NAME | |
| Author | Kaelbling, Leslie Pack, |
| 245 10 - TITLE STATEMENT | |
| Title | Learning in embedded systems / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 PDF (xx, 200 pages) : |
| 490 1# - SERIES STATEMENT | |
| Series statement | Report ; |
| 500 ## - GENERAL NOTE | |
| Remark 1 | Cover title. |
| 500 ## - GENERAL NOTE | |
| Remark 1 | "June 1990." |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Learning to perform complex action strategies is an important problem in the fields of artificial intelligence, robotics, and machine learning. Filled with interesting new experimental results, Learning in Embedded Systems explores algorithms that learn efficiently from trial-and error experience with an external world. It is the first detailed exploration of the problem of learning action strategies in the context of designing embedded systems that adapt their behavior to a complex, changing environment; such systems include mobile robots, factory process controllers, and long-term software databases.Kaelbling investigates a rapidly expanding branch of machine learning known as reinforcement learning, including the important problems of controlled exploration of the environment, learning in highly complex environments, and learning from delayed reward. She reviews past work in this area and presents a number of significant new results. These include the intervalestimation algorithm for exploration, the use of biases to make learning more efficient in complex environments, a generate-and-test algorithm that combines symbolic and statistical processing into a flexible learning method, and some of the first reinforcement-learning experiments with a real robot.Leslie Pack Kaelbling is Assistant Professor in the Computer Science Department at Brown University. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Programming. |
| 856 42 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=6267472 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Stanford, Calif. : |
| -- | Dept. of Computer Science, Stanford University, |
| -- | [c1990] |
| 264 #2 - | |
| -- | [Piscataqay, New Jersey] : |
| -- | IEEE Xplore, |
| -- | [2008] |
| 336 ## - | |
| -- | text |
| -- | rdacontent |
| 337 ## - | |
| -- | electronic |
| -- | isbdmedia |
| 338 ## - | |
| -- | online resource |
| -- | rdacarrier |
| 588 ## - | |
| -- | Description based on PDF viewed 12/24/2015. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Embedded computer systems |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer algorithms. |
No items available.