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Andrea Tacchetti · SciRah

Researcher profile · Semantic Scholar

Andrea Tacchetti

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Andrea Tacchetti — researcher profile on SciRah

h-index: 15
Works: 33
Citations: 6,026

Most-cited papers

Relational inductive biases, deep learning, and graph networks
P. Battaglia, Jessica B. Hamrick, V. Bapst, Alvaro Sanchez-Gonzalez +23 more
2018arXiv.org3,818 citations
Semantic Scholar
Gemma: Open Models Based on Gemini Research and Technology
Gemma Team Thomas Mesnard, Cassidy Hardin, Robert Dadashi, Surya Bhupatiraju +103 more
2024arXiv.org1,299 citations
Semantic Scholar
Visual Interaction Networks: Learning a Physics Simulator from Video
Nicholas Watters, Daniel Zoran, T. Weber, P. Battaglia +2 more
2017Neural Information Processing Systems303 citations
Semantic Scholar
Human-centred mechanism design with Democratic AI
R. Koster, Jan Balaguer, Andrea Tacchetti, Ari Weinstein +7 more
2022Nature Human Behaviour122 citations Open access
Semantic Scholar
Relational Forward Models for Multi-Agent Learning
Andrea Tacchetti, H. F. Song, P. Mediano, V. Zambaldi +5 more
2018International Conference on Learning Representations85 citations
Semantic Scholar
Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy
János Kramár, Tom Eccles, I. Gemp, Andrea Tacchetti +4 more
2022Nature Communications59 citations Open access
Semantic Scholar
Learning to Play No-Press Diplomacy with Best Response Policy Iteration
Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, J'anos Kram'ar +10 more
2020Neural Information Processing Systems50 citations
Semantic Scholar
Scaffolding cooperation in human groups with deep reinforcement learning
Kevin R. McKee, Andrea Tacchetti, Michiel A. Bakker, Jan Balaguer +3 more
2023Nature Human Behaviour41 citations Open access
Semantic Scholar
Language Agents as Digital Representatives in Collective Decision-Making
Daniel Jarrett, Mîruna Pislar, Michiel A. Bakker, Michael Henry Tessler +5 more
2025arXiv.org31 citations
Semantic Scholar
A Neural Architecture for Designing Truthful and Efficient Auctions
Andrea Tacchetti, DJ Strouse, M. Garnelo, T. Graepel +1 more
2019arXiv.org31 citations
Semantic Scholar
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent
I. Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach +5 more
2021Adaptive Agents and Multi-Agent Systems26 citations
Semantic Scholar
D3C: Reducing the Price of Anarchy in Multi-Agent Learning
I. Gemp, Kevin R. McKee, Richard Everett, Edgar A. Duéñez-Guzmán +3 more
2020Adaptive Agents and Multi-Agent Systems24 citations
Semantic Scholar
Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers
Luke Marris, I. Gemp, Thomas W. Anthony, Andrea Tacchetti +2 more
2022Neural Information Processing Systems22 citations Open access
Semantic Scholar
The Good Shepherd: An Oracle Agent for Mechanism Design
Jan Balaguer, R. Koster, C. Summerfield, Andrea Tacchetti
2022arXiv.org22 citations
Semantic Scholar
Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning
Justin Fu, Andrea Tacchetti, J. Pérolat, Yoram Bachrach
2021Journal of Artificial Intelligence Research19 citations Open access
Semantic Scholar
Scaling Opponent Shaping to High Dimensional Games
Akbir Khan, Timon Willi, Newton Kwan, Andrea Tacchetti +4 more
2023Adaptive Agents and Multi-Agent Systems15 citations
Semantic Scholar
Deep reinforcement learning can promote sustainable human behaviour in a common-pool resource problem
Raphael Koster, Mîruna Pislar, Andrea Tacchetti, Jan Balaguer +6 more
2025Nature Communications12 citations Open access
Semantic Scholar
Deep mechanism design: Learning social and economic policies for human benefit
Andrea Tacchetti, Raphael Koster, Jan Balaguer, Le-Qi Liu +5 more
2025Proceedings of the National Academy of Sciences of the United States of America11 citations
Semantic Scholar
Designing all-pay auctions using deep learning and multi-agent simulation
I. Gemp, Thomas W. Anthony, János Kramár, Tom Eccles +2 more
2022Scientific Reports11 citations Open access
Semantic Scholar
Generative Adversarial Equilibrium Solvers
Denizalp Goktas, D. Parkes, I. Gemp, Luke Marris +4 more
2023International Conference on Learning Representations10 citations Open access
Semantic Scholar
Learning Truthful, Efficient, and Welfare Maximizing Auction Rules
Andrea Tacchetti, DJ Strouse, M. Garnelo, T. Graepel +1 more
20198 citations
Semantic Scholar
Human-centered mechanism design with Democratic AI
Raphael Koster, Jan Balaguer, Andrea Tacchetti, Ari Weinstein +7 more
2022arXiv.org6 citations
Semantic Scholar
Should I tear down this wall? Optimizing social metrics by evaluating novel actions
J'anos Kram'ar, N. Rabinowitz, Tom Eccles, Andrea Tacchetti
2020COIN@AAMAS6 citations Open access
Semantic Scholar
HCMD-zero: Learning Value Aligned Mechanisms from Data
Jan Balaguer, R. Koster, Ari Weinstein, Lucy Campbell-Gillingham +3 more
2022arXiv.org5 citations
Semantic Scholar
Using deep reinforcement learning to promote sustainable human behaviour on a common pool resource problem
Raphael Koster, Mîruna Pislar, Andrea Tacchetti, Jan Balaguer +6 more
2024arXiv.org4 citations
Semantic Scholar
Developing, evaluating and scaling learning agents in multi-agent environments
I. Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand +23 more
2022AI Communications4 citations Open access
Semantic Scholar
Publisher Correction: Human-centred mechanism design with Democratic AI
R. Koster, Jan Balaguer, Andrea Tacchetti, Ari Weinstein +7 more
2022Nature Human Behaviour3 citations Open access
Semantic Scholar
LanczosNet : Multi-Scale Deep Graph Convolutional Networks
G. Bakir, B. Schölkopf, P. Battaglia, Jessica B. Hamrick +10 more
20183 citations
Semantic Scholar
Rethinking Teacher-Student Curriculum Learning through the Cooperative Mechanics of Experience
Manfred Diaz, Liam Paull, Andrea Tacchetti
2024Trans. Mach. Learn. Res.2 citations
Semantic Scholar
Leave Graphs Alone: Addressing Over-Squashing without Rewiring
Mateusz Malinowski, Andrea Tacchetti, D. Raposo, A. Santoro +8 more
20221 citations
Semantic Scholar
Neural Design of Contests and All-Pay Auctions using Multi-Agent Simulation
Thomas W. Anthony, I. Gemp, János Kramár, Tom Eccles +2 more
20190 citations
Semantic Scholar
Formality Favored: Unraveling the Learning Preferences of Large Language Models on Data with Conflicting Knowledge
Josh Achiam, Steven Adler, Lama Sandhini Agarwal, Ilge Akkaya +496 more
0 citations
Semantic Scholar
Arc Representation for Graph-based Dependency Parsing
P. Battaglia, Jessica B. Hamrick, V. Bapst, Á. Sánchez-González +202 more
0 citations
Semantic Scholar

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