Negotiating Multi-Issue e-Market Auction through Fuzzy Attitudes

The online auctions are one of the most effective ways of negotiation of salable goods over the Internet. To be successful in open multi-agent environments, agents must be capable of adapting different strategies and tactics to their prevailing circumstances. This paper presents a software test-bed for studying autonomous bidding strategies in simulated auctions for procuring goods. It shows that agents' bidding strategy explore the attitudes and behaviors that help agents to manage dynamic assessment of alternative prices of goods given the different scenario conditions