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http://dspace.mediu.edu.my:8181/xmlui/handle/10261/2984Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Fulbright Commission | - |
| dc.contributor | Plan Nacional de Investigación Científica y Desarrollo (España) | - |
| dc.contributor | Generalidad de Cataluña | - |
| dc.creator | Busquets, Dídac | - |
| dc.creator | Lopez de Mantaras, Ramon | - |
| dc.creator | Sierra, Carles | - |
| dc.creator | Dietterich, Thomas G. | - |
| dc.date | 2008-02-19T11:44:28Z | - |
| dc.date | 2008-02-19T11:44:28Z | - |
| dc.date | 2002 | - |
| dc.date.accessioned | 2017-01-31T01:00:12Z | - |
| dc.date.available | 2017-01-31T01:00:12Z | - |
| dc.identifier | Topics in Artificial Intelligence, 5th Catalonian Conference on AI, CCIA 2002 Castellón, Spain, October 2002. Proceedings. Lecture Notes in Artificial Intelligence Vol. 2504, p.p.: 269-281, Springer-Verlag, 2002. | - |
| dc.identifier | 0302-9743 | - |
| dc.identifier | http://hdl.handle.net/10261/2984 | - |
| dc.identifier.uri | http://dspace.mediu.edu.my:8181/xmlui/handle/10261/2984 | - |
| dc.description | La publicación original está disponible en www.springerlink.com. | - |
| dc.description | This paper extends a navigation system implemented as a multi-agent system (MAS). The arbitration mechanism controlling the interactions between the agents was based on manually-tuned bidding functions. A difficulty with hand-tuning is that it is hard to handle situations involving complex tradeoffs. In this paper we explore the suitability of reinforcement learning for automatically tuning agents within a MAS to optimize a complex tradeoff, namely the camera use. | - |
| dc.description | Fullbright Joint Research Project and Plan Nacional Project DPI 2000-1352-C02-02. Dídac Busquets holds the CIRIT doctoral scholarship 2000FI-00191. | - |
| dc.description | Peer reviewed | - |
| dc.format | 240583 bytes | - |
| dc.format | application/pdf | - |
| dc.language | eng | - |
| dc.publisher | Springer | - |
| dc.rights | openAccess | - |
| dc.subject | Artificial Intelligence | - |
| dc.subject | Machine Learning | - |
| dc.subject | Robotics | - |
| dc.subject | Multiagent Systems | - |
| dc.subject | Fuzzy Logic | - |
| dc.title | A Multi-Agent Architecture Integrating Learning and Fuzzy Techniques for Landmark-Based Robot Navigation | - |
| dc.type | Comunicación de congreso | - |
| Appears in Collections: | Digital Csic | |
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