Enabling Negotiating Agents to Explore Very Large Outcome Spaces

This work presents BIDS (Bidding using Diversied Search), an algorithm that can be used by negotiating agents to search very large outcome spaces. BIDS provides a balance between being rapid, accurate, diverse, and scalable search, allowing agents to search spaces with as many as 10250 possible outcomes on very run-of-the-mill hardware. We<br/...

Learning about the opponent in automated bilateral negotiation: A comprehensive survey of opponent modeling techniques

A negotiation between agents is typically an incomplete information game, where the agents initially do not know their opponent’s preferences or strategy. This poses a challenge, as efficient and effective negotiation requires the bidding agent to take the other’s wishes and future behavior into account when deciding on a proposal. Therefore, in...

GENIUS: An integrated environment for supporting the design of generic automated negotiators

The design of automated negotiators has been the focus of abundant research in recent years. However, due to difficulties involved in creating generalized agents that can negotiate in several domains and against human counterparts, many automated negotiators are domain specific and their behavior cannot be generalized for other domains. Some of...