Abstract:
The online auctions are one of the most effective
ways of negotiation of salable goods over the internet.
To be successful in open multiagent 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.
