Human-Agent Cooperation in Bridge Bidding

2020-11-28 · Edward Lockhart, Neil Burch, Nolan Bard, Sebastian Borgeaud, Tom Eccles, Lucas Smaira, Ray Smith

We introduce a human-compatible reinforcement-learning approach to a cooperative game, making use of a third-party hand-coded human-compatible bot to generate initial training data and to perform initial evaluation. Our learning approach consists of imitation learning, search, and policy iteration. Our trained agents achieve a new state-of-the-art for bridge bidding in three settings: an agent playing in partnership with a copy of itself; an agent partnering a pre-existing bot; and an agent partnering a human player.

📄 PDF Abstract BibTeX arXiv:2011.14124

Code (0)

등록된 구현이 없습니다.

Tasks

Imitation Learningreinforcement-learning Reinforcement Learning (RL)

A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising

2021-06-11 · Chao Wen, Miao Xu, Zhilin Zhang, Zhenzhe Zheng 외

In online advertising, auto-bidding has become an essential tool for advertisers to optimize their preferred ad performance metrics by simply expressing high-level campaign objectives and constraints. Previous works desi…

Multi-agent Reinforcement Learning

Simple is Better: Training an End-to-end Contract Bridge Bidding Agent without Human Knowledge

2019-09-25 · Qucheng Gong, Yu Jiang, Yuandong Tian

Contract bridge is a multi-player imperfect-information game where one partnership collaborate with each other to compete against the other partnership. The game consists of two phases: bidding and playing. While playing…

Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising

2018-02-27 · Junqi Jin, Chengru Song, Han Li, Kun Gai 외

Real-time advertising allows advertisers to bid for each impression for a visiting user. To optimize specific goals such as maximizing revenue and return on investment (ROI) led by ad placements, advertisers not only nee…

Clustering Multi-agent Reinforcement Learning reinforcement-learning Reinforcement Learning+1

Automatic Bridge Bidding Using Deep Reinforcement Learning

2016-07-12 · Chih-Kuan Yeh, Hsuan-Tien Lin

Bridge is among the zero-sum games for which artificial intelligence has not yet outperformed expert human players. The main difficulty lies in the bidding phase of bridge, which requires cooperative decision making unde…

Decision Making Deep Reinforcement Learning reinforcement-learning Reinforcement Learning+1

Bidding in Spades

2019-12-24 · Gal Cohensius, Reshef Meir, Nadav Oved, Roni Stern

We present a Spades bidding algorithm that is superior to recreational human players and to publicly available bots. Like in Bridge, the game of Spades is composed of two independent phases, \textit{bidding} and \textit{…