Abstract:
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.
