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04/10/2023
MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning
We study how a principal can efficiently and effectively intervene on th...
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03/25/2022
Using Reinforcement Learning to Study Platform Economies under Market Shocks
Driven by rapid digitization and expansive internet access, market-drive...
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01/18/2022
Solving Dynamic Principal-Agent Problems with a Rationally Inattentive Principal
Principal-Agent (PA) problems describe a broad class of economic relatio...
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01/03/2022
Analyzing Micro-Founded General Equilibrium Models with Many Agents using Deep Reinforcement Learning
Real economies can be modeled as a sequential imperfect-information game...
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12/06/2021
Simulation Intelligence: Towards a New Generation of Scientific Methods
The original "Seven Motifs" set forth a roadmap of essential methods for...
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08/31/2021
WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU
Deep reinforcement learning (RL) is a powerful framework to train decisi...
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08/06/2021
Building a Foundation for Data-Driven, Interpretable, and Robust Policy Design using the AI Economist
Optimizing economic and public policy is critical to address socioeconom...
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08/05/2021
The AI Economist: Optimal Economic Policy Design via Two-level Deep Reinforcement Learning
AI and reinforcement learning (RL) have improved many areas, but are not...
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06/10/2021
ERMAS: Becoming Robust to Reward Function Sim-to-Real Gaps in Multi-Agent Simulations
Multi-agent simulations provide a scalable environment for learning poli...
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01/13/2021
Robustness Gym: Unifying the NLP Evaluation Landscape
Despite impressive performance on standard benchmarks, deep neural netwo...
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12/11/2020
The Rise of AI-Driven Simulators: Building a New Crystal Ball
The use of computational simulation is by now so pervasive in society th...
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05/02/2020
ESPRIT: Explaining Solutions to Physical Reasoning Tasks
Neural networks lack the ability to reason about qualitative physics and...
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04/28/2020
The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies
Tackling real-world socio-economic challenges requires designing and tes...
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11/04/2019
Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards
While using shaped rewards can be beneficial when solving sparse reward ...
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10/28/2019
Sketch-Fill-A-R: A Persona-Grounded Chit-Chat Generation Framework
Human-like chit-chat conversation requires agents to generate responses ...
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07/01/2019
Learning World Graphs to Accelerate Hierarchical Reinforcement Learning
In many real-world scenarios, an autonomous agent often encounters vario...
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05/29/2019
On the Generalization Gap in Reparameterizable Reinforcement Learning
Understanding generalization in reinforcement learning (RL) is a signifi...
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01/30/2019
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation
Missing value imputation is a fundamental problem in modeling spatiotemp...
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03/20/2018
Generative Multi-Agent Behavioral Cloning
We propose and study the problem of generative multi-agent behavioral cl...
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03/11/2018
Detecting Adversarial Examples via Neural Fingerprinting
Deep neural networks are vulnerable to adversarial examples, which drama...
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02/19/2018
Multi-resolution Tensor Learning for Large-Scale Spatial Data
High-dimensional tensor models are notoriously computationally expensive...
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10/06/2017
Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories
We propose a novel method for effective retrieval of multi-agent spatiot...
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04/15/2016
