Search Results for author: Raphael Koster

Found 9 papers, 4 papers with code

The Good Shepherd: An Oracle Agent for Mechanism Design

no code implementations21 Feb 2022 Jan Balaguer, Raphael Koster, Christopher Summerfield, Andrea Tacchetti

Our results show that our mechanisms are able to shepherd the participants strategies towards favorable outcomes, indicating a path for modern institutions to effectively and automatically influence the strategies and behaviors of their constituents.

HCMD-zero: Learning Value Aligned Mechanisms from Data

no code implementations21 Feb 2022 Jan Balaguer, Raphael Koster, Ari Weinstein, Lucy Campbell-Gillingham, Christopher Summerfield, Matthew Botvinick, Andrea Tacchetti

Our analysis shows HCMD-zero consistently makes the mechanism policy more and more likely to be preferred by human participants over the course of training, and that it results in a mechanism with an interpretable and intuitive policy.

Role of Human-AI Interaction in Selective Prediction

1 code implementation13 Dec 2021 Elizabeth Bondi, Raphael Koster, Hannah Sheahan, Martin Chadwick, Yoram Bachrach, Taylan Cemgil, Ulrich Paquet, Krishnamurthy Dvijotham

Using real-world conservation data and a selective prediction system that improves expected accuracy over that of the human or AI system working individually, we show that this messaging has a significant impact on the accuracy of human judgements.

Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot

no code implementations14 Jul 2021 Joel Z. Leibo, Edgar Duéñez-Guzmán, Alexander Sasha Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charles Beattie, Igor Mordatch, Thore Graepel

Existing evaluation suites for multi-agent reinforcement learning (MARL) do not assess generalization to novel situations as their primary objective (unlike supervised-learning benchmarks).

Multi-agent Reinforcement Learning reinforcement-learning +2

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