Towards genetically optimised responsive negotiation agents

Raymond Y. K. Lau; Maolin Tang; On Wong

doi:10.1109/IAT.2004.1342958

Towards genetically optimised responsive negotiation agents

Raymond Y. K. Lau
, Maolin Tang
, On Wong

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

29 Citations (Scopus)

Abstract

Real-world negotiations are characterised by combinatorially complex negotiation spaces, tough deadlines, bounded agent rationality, very limited information about the opponents, and volatile negotiator preferences. Classical negotiation models fail to address most of these issues. This paper illustrates our practical negotiation agents which are empowered by an effective and efficient genetic algorithm to deal with complex, incomplete, and dynamic negotiation spaces arising in real-world applications. Initial experiment demonstrates that our genetically optimised adaptive negotiation agents outperform a theoretically optimal negotiation model when time pressure exists. Our research work opens the door to the development of responsive and adaptive negotiation agents for real-world applications. © 2004 IEEE.

Original language	English
Title of host publication	Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004
Pages	295-301
DOIs	https://doi.org/10.1109/IAT.2004.1342958
Publication status	Published - 2004
Externally published	Yes
Event	Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004 - Beijing, China Duration: 20 Sept 2004 → 24 Sept 2004

Conference

Conference	Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004
Place	China
City	Beijing
Period	20/09/04 → 24/09/04

Research Keywords

Adaptive Agents
Automated Negotiation
Genetic Algorithm

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10.1109/IAT.2004.1342958

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title = "Towards genetically optimised responsive negotiation agents",

abstract = "Real-world negotiations are characterised by combinatorially complex negotiation spaces, tough deadlines, bounded agent rationality, very limited information about the opponents, and volatile negotiator preferences. Classical negotiation models fail to address most of these issues. This paper illustrates our practical negotiation agents which are empowered by an effective and efficient genetic algorithm to deal with complex, incomplete, and dynamic negotiation spaces arising in real-world applications. Initial experiment demonstrates that our genetically optimised adaptive negotiation agents outperform a theoretically optimal negotiation model when time pressure exists. Our research work opens the door to the development of responsive and adaptive negotiation agents for real-world applications. {\textcopyright} 2004 IEEE.",

keywords = "Adaptive Agents, Automated Negotiation, Genetic Algorithm",

author = "Lau, \{Raymond Y. K.\} and Maolin Tang and On Wong",

year = "2004",

doi = "10.1109/IAT.2004.1342958",

language = "English",

isbn = "0769521010",

pages = "295--301",

booktitle = "Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004",

note = "Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004 ; Conference date: 20-09-2004 Through 24-09-2004",

}

Towards genetically optimised responsive negotiation agents. / Lau, Raymond Y. K.; Tang, Maolin; Wong, On.
Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004. 2004. p. 295-301.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

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AB - Real-world negotiations are characterised by combinatorially complex negotiation spaces, tough deadlines, bounded agent rationality, very limited information about the opponents, and volatile negotiator preferences. Classical negotiation models fail to address most of these issues. This paper illustrates our practical negotiation agents which are empowered by an effective and efficient genetic algorithm to deal with complex, incomplete, and dynamic negotiation spaces arising in real-world applications. Initial experiment demonstrates that our genetically optimised adaptive negotiation agents outperform a theoretically optimal negotiation model when time pressure exists. Our research work opens the door to the development of responsive and adaptive negotiation agents for real-world applications. © 2004 IEEE.

KW - Adaptive Agents

KW - Automated Negotiation

KW - Genetic Algorithm

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M3 - RGC 32 - Refereed conference paper (with host publication)

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SN - 9780769521015

SP - 295

EP - 301

BT - Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004

T2 - Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004

Y2 - 20 September 2004 through 24 September 2004

ER -

Towards genetically optimised responsive negotiation agents

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Research Keywords

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