Opponent Modeling in Automated Bilateral Negotiation: Can Machine Learning Techniques Outperform State-of-the-Art Heuristic Techniques?

Automated negotiation agents can highly benefit from learning their opponent’s preferences. Multiple algorithms have been developed with the two main categories being: heuristic techniques and machine learning techniques. Historically, heuristic techniques have dominated the field, but with the recent development in the field of machine learning...

Actor-critic reinforcement learning for bidding in bilateral negotiation

Designing an effective and intelligent bidding strategy is one of the most compelling research challenges in automated negotiation, where software agents negotiate with each other to find a mutual agreement when there is a conflict of interests. Instead of designing a hand-crafted decision-making module, this work proposes a novel bidding...

Deep reinforcement learning for acceptance strategy in bilateral negotiations

This paper introduces an acceptance strategy based on reinforcement learning for automated bilateral negotiation, where negotiating agents bargain on multiple issues in a variety of negotiation scenarios. Several acceptance strategies based on predefined rules have been introduced in the automated negotiation literature. Those rules mostly...

Modelling the Emergence of Functioning Natural Gas Wholesale Markets

The European Commission considers liberalized and liquid natural gas wholesale markets as a priority. Agent-based models are considered suited to provide insight in what market conditions contribute to the emergence of functioning natural gas wholesale markets. We present an abstraction of the natural gas market to explore the emergence of...

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...

Approximating the Qualitative Vickrey Auction by a Negotiation Protocol

A result of Bulow and Klemperer has suggested that auctions may be a better tool to obtain an efficient outcome than negotiation. For example, some auction mechanisms can be shown to be efficient and strategy-proof. However, they generally also require that additional constraints are met which are not always easy to guarantee in practice. It...

Qualitative One-to-Many Multi-Issue Negotiation: Approximating the QVA

When there is one buyer interested in obtaining a service from one of a set of sellers, multi-attribute or multi-issue auctions can ensure an allocation that is efficient. Even when there is no transferable utility (e.g., money), a recent qualitative version of the Vickrey auction may be used, the QVA, to obtain a Pareto-efficient outcome where...

An agent architecture for multi-attribute negotiation using incomplete preference information