Andrea Tacchetti

Orcid: 0000-0001-9311-9171

According to our database1, Andrea Tacchetti authored at least 30 papers between 2013 and 2024.

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Bibliography

2024
Teamwork Reinforcement Learning With Concave Utilities.
IEEE Trans. Mob. Comput., May, 2024

Gemma: Open Models Based on Gemini Research and Technology.
CoRR, 2024

2023
Scaling Opponent Shaping to High Dimensional Games.
CoRR, 2023

Generative Adversarial Equilibrium Solvers.
CoRR, 2023

2022
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments.
CoRR, 2022

The Good Shepherd: An Oracle Agent for Mechanism Design.
CoRR, 2022

HCMD-zero: Learning Value Aligned Mechanisms from Data.
CoRR, 2022

Human-centered mechanism design with Democratic AI.
CoRR, 2022

Developing, evaluating and scaling learning agents in multi-agent environments.
AI Commun., 2022

Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

D3C: Reducing the Price of Anarchy in Multi-Agent Learning.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021
Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning.
J. Artif. Intell. Res., 2021

2020
Learning to Play No-Press Diplomacy with Best Response Policy Iteration.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Should I Tear down This Wall? Optimizing Social Metrics by Evaluating Novel Actions.
Proceedings of the Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XIII, 2020

2019
A Neural Architecture for Designing Truthful and Efficient Auctions.
CoRR, 2019

Relational Forward Models for Multi-Agent Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Relational Forward Models for Multi-Agent Learning.
CoRR, 2018

Relational inductive biases, deep learning, and graph networks.
CoRR, 2018

Trading robust representations for sample complexity through self-supervised visual experience.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Learning invariant representations of actions and faces.
PhD thesis, 2017

Invariant recognition drives neural representations of action sequences.
PLoS Comput. Biol., 2017

Visual Interaction Networks.
CoRR, 2017

Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets.
CoRR, 2017

Visual Interaction Networks: Learning a Physics Simulator from Video.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Representation Learning from Orbit Sets for One-Shot Classification.
Proceedings of the 2017 AAAI Spring Symposia, 2017

2016
Unsupervised learning of invariant representations.
Theor. Comput. Sci., 2016

2014
Regularization by Early Stopping for Online Learning Algorithms.
CoRR, 2014

2013
GURLS: a least squares library for supervised learning.
J. Mach. Learn. Res., 2013

Unsupervised Learning of Invariant Representations in Hierarchical Architectures.
CoRR, 2013


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