Andrea Tacchetti

41 papers A* 4A 3Journal 29Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Language Agents as Digital Representatives in Collective Decision-Making.
CoRR
Daniel Jarrett, Miruna Pîslar, Michiel A. Bakker, Michael Henry Tessler, Raphael Köster, Jan Balaguer, Romuald Elie, Christopher Summerfield, Andrea Tacchetti
2024 A* conf
Generative Adversarial Equilibrium Solvers.
ICLR
Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti
2024 J jnl
Rethinking Teacher-Student Curriculum Learning through the Cooperative Mechanics of Experience.
CoRR
Manfred Diaz, Liam Paull, Andrea Tacchetti
2024 J jnl
Rethinking Teacher-Student Curriculum Learning through the Cooperative Mechanics of Experience.
Trans. Mach. Learn. Res.
Manfred Diaz, Liam Paull, Andrea Tacchetti
2024 A conf
Scaling Opponent Shaping to High Dimensional Games.
AAMAS
Akbir Khan, Timon Willi, Newton Kwan, Andrea Tacchetti, Chris Lu, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster
2024 J jnl
Teamwork Reinforcement Learning With Concave Utilities.
IEEE Trans. Mob. Comput.
Zheng Yu, Junyu Zhang, Zheng Wen, Andrea Tacchetti, Mengdi Wang, Ian Gemp
2024 J jnl
Using deep reinforcement learning to promote sustainable human behaviour on a common pool resource problem.
CoRR
Raphael Koster, Miruna Pîslar, Andrea Tacchetti, Jan Balaguer, Leqi Liu, Romuald Elie, Oliver P. Hauser, Karl Tuyls, Matt M. Botvinick, Christopher Summerfield
2023 J jnl
Generative Adversarial Equilibrium Solvers.
CoRR
Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti
2023 J jnl
Scaling Opponent Shaping to High Dimensional Games.
CoRR
Akbir Khan, Timon Willi, Newton Kwan, Andrea Tacchetti, Chris Lu, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster
2022 A conf
D3C: Reducing the Price of Anarchy in Multi-Agent Learning.
AAMAS
Ian Gemp, Kevin R. McKee, Richard Everett, Edgar A. Duéñez-Guzmán, Yoram Bachrach, David Balduzzi, Andrea Tacchetti
2022 J jnl
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments.
CoRR
Ian Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson, Guy Lever, Siqi Liu, Luke Marris, Kevin R. McKee, Paul Muller, Julien Pérolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls
2022 J jnl
Developing, evaluating and scaling learning agents in multi-agent environments.
AI Commun.
Ian Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson, Guy Lever, Siqi Liu, Luke Marris, Kevin R. McKee, Paul Muller, Julien Pérolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls
2022 J jnl
HCMD-zero: Learning Value Aligned Mechanisms from Data.
CoRR
Jan Balaguer, Raphael Koster, Ari Weinstein, Lucy Campbell-Gillingham, Christopher Summerfield, Matthew M. Botvinick, Andrea Tacchetti
2022 J jnl
Human-centered mechanism design with Democratic AI.
CoRR
Raphael Koster, Jan Balaguer, Andrea Tacchetti, Ari Weinstein, Tina Zhu, Oliver P. Hauser, Duncan Williams, Lucy Campbell-Gillingham, Phoebe Thacker, Matthew M. Botvinick, Christopher Summerfield
2022 A conf
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent.
AAMAS
Ian Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár
2022 J jnl
The Good Shepherd: An Oracle Agent for Mechanism Design.
CoRR
Jan Balaguer, Raphael Koster, Christopher Summerfield, Andrea Tacchetti
2022 A* conf
Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers.
NeurIPS
Luke Marris, Ian Gemp, Thomas Anthony, Andrea Tacchetti, Siqi Liu, Karl Tuyls
2022 J jnl
Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers.
CoRR
Luke Marris, Ian Gemp, Thomas W. Anthony, Andrea Tacchetti, Siqi Liu, Karl Tuyls
2021 J jnl
Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning.
J. Artif. Intell. Res.
Justin Fu, Andrea Tacchetti, Julien Pérolat, Yoram Bachrach
2021 J jnl
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent.
CoRR
Ian Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár
2020 J jnl
D3C: Reducing the Price of Anarchy in Multi-Agent Learning.
CoRR
Ian Gemp, Kevin R. McKee, Richard Everett, Edgar A. Duéñez-Guzmán, Yoram Bachrach, David Balduzzi, Andrea Tacchetti
2020 A* conf
Learning to Play No-Press Diplomacy with Best Response Policy Iteration.
NeurIPS
Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach
2020 J jnl
Learning to Play No-Press Diplomacy with Best Response Policy Iteration.
CoRR
Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach
2020 — conf
Should I Tear down This Wall? Optimizing Social Metrics by Evaluating Novel Actions.
COIN(E)@AAMAS
János Kramár, Neil C. Rabinowitz, Tom Eccles, Andrea Tacchetti
2020 J jnl
Should I tear down this wall? Optimizing social metrics by evaluating novel actions.
CoRR
János Kramár, Neil C. Rabinowitz, Tom Eccles, Andrea Tacchetti
2019 J jnl
A Neural Architecture for Designing Truthful and Efficient Auctions.
CoRR
Andrea Tacchetti, DJ Strouse, Marta Garnelo, Thore Graepel, Yoram Bachrach
2019 — conf
Relational Forward Models for Multi-Agent Learning.
ICLR (Poster)
Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, János Kramár, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia
2018 J jnl
Relational Forward Models for Multi-Agent Learning.
CoRR
Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia
2018 J jnl
Relational inductive biases, deep learning, and graph networks.
CoRR
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinícius Flores Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Çaglar Gülçehre, H. Francis Song, Andrew J. Ballard, Justin Gilmer, George E. Dahl, Ashish Vaswani, Kelsey R. Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matthew M. Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu
2018 A* conf
Trading robust representations for sample complexity through self-supervised visual experience.
NeurIPS
Andrea Tacchetti, Stephen Voinea, Georgios Evangelopoulos
2017 J jnl
Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets.
CoRR
Andrea Tacchetti, Stephen Voinea, Georgios Evangelopoulos
2017 J jnl
Invariant recognition drives neural representations of action sequences.
PLoS Comput. Biol.
Andrea Tacchetti, Leyla Isik, Tomaso A. Poggio
2017 — —
Learning invariant representations of actions and faces.
Andrea Tacchetti
2017 — conf
Representation Learning from Orbit Sets for One-Shot Classification.
AAAI Spring Symposia
Andrea Tacchetti, Stephen Voinea, Georgios Evangelopoulos, Tomaso A. Poggio
2017 J jnl
Visual Interaction Networks.
CoRR
Nicholas Watters, Andrea Tacchetti, Theophane Weber, Razvan Pascanu, Peter W. Battaglia, Daniel Zoran
2017 — conf
Visual Interaction Networks: Learning a Physics Simulator from Video.
NIPS
Nicholas Watters, Daniel Zoran, Theophane Weber, Peter W. Battaglia, Razvan Pascanu, Andrea Tacchetti
2016 J jnl
Unsupervised learning of invariant representations.
Theor. Comput. Sci.
Fabio Anselmi, Joel Z. Leibo, Lorenzo Rosasco, Jim Mutch, Andrea Tacchetti, Tomaso A. Poggio
2014 J jnl
Regularization by Early Stopping for Online Learning Algorithms.
CoRR
Lorenzo Rosasco, Andrea Tacchetti, Silvia Villa
2013 J jnl
GURLS: a Least Squares Library for Supervised Learning
CoRR
Andrea Tacchetti, Pavan Kumar Mallapragada, Matteo Santoro, Lorenzo Rosasco
2013 J jnl
GURLS: a least squares library for supervised learning.
J. Mach. Learn. Res.
Andrea Tacchetti, Pavan Kumar Mallapragada, Matteo Santoro, Lorenzo Rosasco
2013 J jnl
Unsupervised Learning of Invariant Representations in Hierarchical Architectures.
CoRR
Fabio Anselmi, Joel Z. Leibo, Lorenzo Rosasco, Jim Mutch, Andrea Tacchetti, Tomaso A. Poggio