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Article
Open AccessScaffolding cooperation in human groups with deep reinforcement learning
Effective approaches to encouraging group cooperation are still an open challenge. Here we apply recent advances in deep learning to structure networks of human participants playing a group cooperation game. W...
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Article
Open AccessNegotiation and honesty in artificial intelligence methods for the board game of Diplomacy
The success of human civilization is rooted in our ability to cooperate by communicating and making joint plans. We study how artificial agents may use communication to better cooperate in Diplomacy, a long-st...
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Article
Open AccessDesigning all-pay auctions using deep learning and multi-agent simulation
We propose a multi-agent learning approach for designing crowdsourcing contests and All-Pay auctions. Prizes in contests incentivise contestants to expend effort on their entries, with different prize allocati...
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Article
Open AccessHuman-centred mechanism design with Democratic AI
Building artificial intelligence (AI) that aligns with human values is an unsolved problem. Here we developed a human-in-the-loop research pipeline called Democratic AI, in which reinforcement learning is used...
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Article
Open AccessPublisher Correction: Human-centred mechanism design with Democratic AI
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Chapter and Conference Paper
Should I Tear down This Wall? Optimizing Social Metrics by Evaluating Novel Actions
One of the fundamental challenges of governance is deciding when and how to intervene in multi-agent systems in order to impact group-wide metrics of success. This is particularly challenging when proposed int...
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Chapter
Invariant Recognition Predicts Tuning of Neurons in Sensory Cortex
Tuning properties of simple cells in cortical V1 can be described in terms of a “universal shape” characterized quantitatively by parameter values which hold across different species (Jones and Palmer 1987; Ringa...
