Authors:
Wafa Ghonaim
1
;
Hamada Ghenniwa
1
and
Weiming Shen
2
Affiliations:
1
Western University, Canada
;
2
National Research Council Canada, Canada
Keyword(s):
Smart Exchange, Double Auction, GSP Auction, Reverse GSP Auction, GSP Matching, Bidding Language, Strategic Rules, Bidding Lifecycle, Preference Elicitation, Preference Formulation, Winner Determination.
Related
Ontology
Subjects/Areas/Topics:
Agent Communication Languages
;
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Auctions and Markets
;
Cooperation and Coordination
;
Distributed and Mobile Software Systems
;
Economic Agent Models
;
Enterprise Information Systems
;
Formal Methods
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Multi-Agent Systems
;
Planning and Scheduling
;
Simulation and Modeling
;
Software Engineering
;
Symbolic Systems
Abstract:
The landscapes of e-marketplaces are changing profoundly, evident in the phenomenal growth and potential of online services, consumers, and enabling mobile technologies. However, it is unleashing grave concerns about sustainability due to the fierce competitions, fuzzy dynamics and rapidly shifting powers. While it is attributed to the game-theoretic economics and computation complexities of the decentralized combinatorial allocation problem, this work establishes, denying e-traders expressing fair strategic choice is unfounded of adverse strategic risk. In fact, free market dynamics realize impact of smart learning on strategic conduct. The fact strategic rules enable faster consumer-to-market bidding lifecycle is another compelling factor. Hence, the work introduces the novel rule-based bidding language and GSPM double auction for the smart exchange that facilitates expressions of strategic rules, while uniquely exploits forward and reverse GSP auctions for efficient, tractable, st
able, and budget balanced e-marketplace. The e-marketplace deliberates on rules for effective preference elicitation, while bringing self-prosperity in socially efficient ecosystem.
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