In online and dynamic e-commerce environments, it is beneficial for parties to consider each
other's preferences in carrying out transactions. This is especially important when parties are …

We consider automated negotiation as a process carried out by software agents to reach a
consensus. To automate negotiation, we expect agents to understand their user's …

In automated negotiation, information gained about an opponent's preference profile by
means of learning techniques may significantly improve an agent's negotiation performance …

User preference learning is an important process in automated negotiation, because only
when the negotiating agents are able to fully grasp the user preference information can the …

Autonomous agents can negotiate on behalf of buyers and sellers to make a contract in the
e-marketplace. In bilateral negotiation, they need to find a joint agreement by satisfying each …

Automated negotiation is a process in which autonomous agents negotiate with the
opponents to achieve some specific purposes for their users, such as maximising the users' …

A wide range of algorithms have been developed for various types of automated negotiation.
In developing such algorithms the main focus has been on their efficiency and their …

An agent engaged in multi-issue automated negotiation can benefit greatly from learning
about its opponent's preferences. Knowledge of the opponent's preferences can help the …

Automated negotiation by artificial adaptive agents (AAAs) holds great promise for electronic
commerce, but non-trivial, practical issues remain. Published studies of AAA learning of …

Classical negotiation models are weak in supporting real-world business negotiations
because these models often assume that the preference information of each negotiator is …