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07/17/2023
Reflections from the Workshop on AI-Assisted Decision Making for Conservation
In this white paper, we synthesize key points made during presentations ...
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08/28/2022
Normality-Guided Distributional Reinforcement Learning for Continuous Control
Learning a predictive model of the mean return, or value function, plays...
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10/08/2021
Training Transition Policies via Distribution Matching for Complex Tasks
Humans decompose novel complex tasks into simpler ones to exploit previo...
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06/06/2021
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning
In the predict-then-optimize framework, the objective is to train a pred...
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06/06/2021
Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games
A growing body of work in game theory extends the traditional Stackelber...
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09/14/2020
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security
Conservation efforts in green security domains to protect wildlife and f...
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07/05/2020
Collapsing Bandits and Their Application to Public Health Interventions
We propose and study Collpasing Bandits, a new restless multi-armed band...
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06/22/2020
Game Theory on the Ground: The Effect of Increased Patrols on Deterring Poachers
Applications of artificial intelligence for wildlife protection have foc...
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06/18/2020
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems
Solving optimization problems with unknown parameters often requires lea...
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12/16/2019
AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline
With the maturing of AI and multiagent systems research, we have a treme...
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11/20/2019
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning
Large-scale screening for potential threats with limited resources and c...
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03/03/2019
Decision-Focused Learning of Adversary Behavior in Security Games
Stackelberg security games are a critical tool for maximizing the utilit...
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05/13/2015
