A Deep Reinforcement Learning Approach to Concurrent Bilateral Negotiation

We present a novel negotiation model that allows an agent to learn how to negotiate during concurrent bilateral negotiations in unknown and dynamic e-markets. The agent uses an actor-critic architecture with model-free reinforcement learning to learn a strategy expressed as a deep neural network. We pre-train the strategy by supervision from synthetic market data, thereby decreasing the exploration time required for learning during negotiation. As a result, we can build automated agents for concurrent negotiations that can adapt to different e-market settings without the need to be pre-programmed. Our experimental evaluation shows that our deep reinforcement learning-based agents outperform two existing well-known negotiation strategies in one-to-many concurrent bilateral negotiations for a range of e-market settings

Coordinating the bidding strategy in multiissue multiobject negotiation with single and multiple providers

This paper addresses the problem of flexible procurement of multiple distinct services characterized by multiple nonfunctional characteristics, i.e., quality-of-service attributes. We consider the one-to-many negotiation approach as a flexible method for procuring multiple different services by a buyer agent. We address the problem of coordinating the bidding strategy amongst multiple concurrent negotiations and propose novel dynamic negotiation strategies. The proposed strategies consider the behaviors of the opponents of the current negotiation encounter in managing the local reservation values of the common negotiation issues (attributes) of different services. Most previous works consider the problem of negotiation over a single object characterized by one or more issues. We extend our previous work and investigate a more complex situation where a buyer agent negotiates over multiple distinct services given that each service has multiple negotiation issues and multiple possible providers. The experimental results show evidence for the effectiveness and robustness of our dynamic negotiation strategies under various negotiation environments