From market-driven agents to market-oriented grids (position paper)
ACM SIGecom Exchanges
Equilibrium analyses of market-driven agents
ACM SIGecom Exchanges
A survey of bargaining models for grid resource allocation
ACM SIGecom Exchanges
Agent-Based Control Framework for Distributed Energy Resources Microgrids
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
Relaxed-criteria G-negotiation for Grid resource co-allocation
ACM SIGecom Exchanges
The Use of Cognitive Maps and Case-Based Reasoning for B2B Negotiation
Journal of Management Information Systems
Market-driven agents with uncertain and dynamic outside options
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Decision making of negotiation agents using markov chains
Multiagent and Grid Systems - Negotiation and Scheduling Mechanisms for Multiagent Systems
Retractable contract network for empowerment in workforce scheduling
Multiagent and Grid Systems - Negotiation and Scheduling Mechanisms for Multiagent Systems
Decommitment in multi-resource negotiation
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Adaptive conceding strategies for automated trading agents in dynamic, open markets
Decision Support Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Evolving best-response strategies for market-driven agents using aggregative fitness GA
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Partners selection in multi-agent systems by using linear and non-linear approaches
Transactions on computational science I
Concurrent negotiation and coordination for grid resource coallocation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Grid resource negotiation: survey and new directions
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Agent based e-commerce systems that react to buyers' feedbacks -- A fuzzy approach
International Journal of Approximate Reasoning
Multi-agent asynchronous negotiation based on time-delay
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part I
Strategic agents for multi-resource negotiation
Autonomous Agents and Multi-Agent Systems
Automatic Service Agreement Negotiators in Open Commerce Environments
International Journal of Electronic Commerce
Towards complex negotiation for cloud economy
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
The design and implementation of an intelligent agent-based adaptive bargaining model (ABM)
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Bilateral bargaining with one-sided uncertain reserve prices
Autonomous Agents and Multi-Agent Systems
Tasks for agent-based negotiation teams: Analysis, review, and challenges
Engineering Applications of Artificial Intelligence
A new fuzzy negotiation protocol for grid resource allocation
Journal of Network and Computer Applications
Expectation of trading agent behaviour in negotiation of electronic marketplace
Web Intelligence and Agent Systems
| Hi-index | 0.00 |
Market-driven agents are negotiation agents that react to changing market situations by making adjustable rates of concession. This paper presents 1) the foundations for designing market-driven strategies of agents, 2) a testbed of market-driven agents, 3) experimental results in simulating the market-driven approach, and 4) theoretical analyses of agents' performance in extremely large markets. In determining the amount of concession for each trading cycle, market-driven agents in this research are guided by four mathematical functions of eagerness, remaining trading time, trading opportunity , and competition. At different stages of trading, agents may adopt different trading strategies, and make different rates of concession. Four classes of strategies with respect to remaining trading time are discussed. Trading opportunity is determined by considering: 1) number of trading partners, 2) spreads-differences in utilities between an agent and its trading partners, and 3) probability of completing a deal. While eagerness represents an agent's desire to trade, trading competition is determined by the probability that it is not considered as the most preferred trader by its trading partners. Experimental results and theoretical analyses showed that agents guided by market-driven strategies 1) react to changing market situations by making prudent and appropriate rates of concession, and 2) achieve trading outcomes that correspond to intuitions in real-life trading.