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Volumn 19, Issue 6, 2004, Pages 12-20

Creating an ambient-intelligence environment using embedded agents

Author keywords

[No Author keywords available]

Indexed keywords

AMBIENT INTELLIGENCE; EMBEDDED AGENTS; INCREMENTED SYNCHRONOUS LEARNING (ISL); UBIQUITOUS COMPUTING;

EID: 10944258782     PISSN: 15411672     EISSN: None     Source Type: Journal    
DOI: 10.1109/MIS.2004.61     Document Type: Review
Times cited : (254)

References (6)
  • 1
    • 0010337637 scopus 로고    scopus 로고
    • tech. report, Information Society Technologies Advisory Group (ISTAG), Inst. of Prospective Technological Studies (IPTS)
    • K. Ducatel et al., Scenarios for Ambient Intelligence in 2010, tech. report, Information Society Technologies Advisory Group (ISTAG), Inst. of Prospective Technological Studies (IPTS), 2001.
    • (2001) Scenarios for Ambient Intelligence in 2010
    • Ducatel, K.1
  • 3
    • 10944235806 scopus 로고    scopus 로고
    • Online learning and adaptation for intelligent embedded agents operating in domestic environments
    • Fusion of Soft Computing and Hard Computing for Autonomous Robotic Systems, C. Zhou, D. Maravall, and D. Ruan, eds., Nov.
    • H. Hagras et al., "Online Learning and Adaptation for Intelligent Embedded Agents Operating in Domestic Environments," Fusion of Soft Computing and Hard Computing for Autonomous Robotic Systems, C. Zhou, D. Maravall, and D. Ruan, eds., Physica-Verlag, vol. 116, Nov. 2002, pp. 293-323.
    • (2002) Physica-verlag , vol.116 , pp. 293-323
    • Hagras, H.1
  • 4
    • 0001837431 scopus 로고    scopus 로고
    • Comparing reinforcement learning algorithms applied to crisp and fuzzy learning classifier systems
    • Morgan Kaufmann
    • A. Bonarini, "Comparing Reinforcement Learning Algorithms Applied to Crisp and Fuzzy Learning Classifier Systems," Proc. Genetic and Evolutionary Computation Conf., Morgan Kaufmann, 1999, pp. 52-60.
    • (1999) Proc. Genetic and Evolutionary Computation Conf. , pp. 52-60
    • Bonarini, A.1
  • 5
    • 0037361830 scopus 로고    scopus 로고
    • A hierarchical fuzzy genetic multi-agent architecture for intelligent buildings learning, adaptation and control
    • Mar.
    • H. Hagras et al., "A Hierarchical Fuzzy Genetic Multi-Agent Architecture for Intelligent Buildings Learning, Adaptation and Control," Int'l J. Information Sciences, vol. 150, nos. 1-2, Mar. 2003, pp. 33-54.
    • (2003) Int'l J. Information Sciences , vol.150 , Issue.1-2 , pp. 33-54
    • Hagras, H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.