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06/04/2023
Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in RL
Reinforcement learning agents may sometimes develop habits that are effe...
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06/01/2023
What model does MuZero learn?
Model-based reinforcement learning has drawn considerable interest in re...
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05/29/2023
Towards a Unifying Model of Rationality in Multiagent Systems
Multiagent systems deployed in the real world need to cooperate with oth...
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02/27/2023
Safe Multi-agent Learning via Trapping Regions
One of the main challenges of multi-agent learning lies in establishing ...
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02/07/2023
Uncoupled Learning of Differential Stackelberg Equilibria with Commitments
A natural solution concept for many multiagent settings is the Stackelbe...
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08/30/2022
An Analysis of Abstracted Model-Based Reinforcement Learning
Many methods for Model-based Reinforcement learning (MBRL) provide guara...
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07/01/2022
Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems
Due to its high sample complexity, simulation is, as of today, critical ...
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06/20/2022
On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games
Learning to cooperate with other agents is challenging when those agents...
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04/03/2022
Best-Response Bayesian Reinforcement Learning with Bayes-adaptive POMDPs for Centaurs
Centaurs are half-human, half-AI decision-makers where the AI's goal is ...
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02/17/2022
BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs
While reinforcement learning (RL) has made great advances in scalability...
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02/03/2022
Influence-Augmented Local Simulators: A Scalable Solution for Fast Deep RL in Large Networked Systems
Learning effective policies for real-world problems is still an open cha...
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01/27/2022
Online Planning in POMDPs with Self-Improving Simulators
How can we plan efficiently in a large and complex environment when the ...
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12/30/2021
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning
Inferring reward functions from demonstrations and pairwise preferences ...
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10/09/2021
Multi-Agent MDP Homomorphic Networks
This paper introduces Multi-Agent MDP Homomorphic Networks, a class of n...
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12/21/2020
Difference Rewards Policy Gradients
Policy gradient methods have become one of the most popular classes of a...
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11/16/2020
Analog Circuit Design with Dyna-Style Reinforcement Learning
In this work, we present a learning based approach to analog circuit des...
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11/03/2020
Loss Bounds for Approximate Influence-Based Abstraction
Sequential decision making techniques hold great promise to improve the ...
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10/22/2020
Multi-agent active perception with prediction rewards
Multi-agent active perception is a task where a team of agents cooperati...
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10/21/2020
Influence-Augmented Online Planning for Complex Environments
How can we plan efficiently in real time to control an agent in a comple...
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09/21/2020
Exploiting Submodular Value Functions For Scaling Up Active Perception
In active perception tasks, an agent aims to select sensory actions that...
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06/30/2020
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning
This paper introduces MDP homomorphic networks for deep reinforcement le...
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05/15/2020
Sensor Data for Human Activity Recognition: Feature Representation and Benchmarking
The field of Human Activity Recognition (HAR) focuses on obtaining and a...
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04/27/2020
Diversity in Action: General-Sum Multi-Agent Continuous Inverse Optimal Control
Traffic scenarios are inherently interactive. Multiple decision-makers p...
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03/31/2020
Mimicking Evolution with Reinforcement Learning
Evolution gave rise to human and animal intelligence here on Earth. We a...
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07/22/2019
A Sufficient Statistic for Influence in Structured Multiagent Environments
Making decisions in complex environments is a key challenge in artificia...
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02/20/2019
The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning
Recent years have seen the application of deep reinforcement learning te...
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11/08/2018
Learning from Demonstration in the Wild
Learning from demonstration (LfD) is useful in settings where hand-codin...
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06/18/2018
Beyond Local Nash Equilibria for Adversarial Networks
Save for some special cases, current training methods for Generative Adv...
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06/14/2018
Learning in POMDPs with Monte Carlo Tree Search
The POMDP is a powerful framework for reasoning under outcome and inform...
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12/02/2017
GANGs: Generative Adversarial Network Games
Generative Adversarial Networks (GAN) have become one of the most succes...
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06/22/2016
Structure in the Value Function of Two-Player Zero-Sum Games of Incomplete Information
Zero-sum stochastic games provide a rich model for competitive decision ...
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02/25/2016
Probably Approximately Correct Greedy Maximization
Submodular function maximization finds application in a variety of real-...
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11/30/2015
Scaling POMDPs For Selecting Sellers in E-markets-Extended Version
In multiagent e-marketplaces, buying agents need to select good sellers ...
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11/29/2015
Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs (Extended Version)
Many exact and approximate solution methods for Markov Decision Processe...
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11/29/2015
Solving Transition-Independent Multi-agent MDPs with Sparse Interactions (Extended version)
In cooperative multi-agent sequential decision making under uncertainty,...
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02/18/2015
Influence-Optimistic Local Values for Multiagent Planning --- Extended Version
Recent years have seen the development of methods for multiagent plannin...
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04/04/2014
Scalable Planning and Learning for Multiagent POMDPs: Extended Version
Online, sample-based planning algorithms for POMDPs have shown great pro...
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10/16/2012
Exploiting Structure in Cooperative Bayesian Games
Cooperative Bayesian games (BGs) can model decision-making problems for ...
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10/31/2011
Optimal and Approximate Q-value Functions for Decentralized POMDPs
Decision-theoretic planning is a popular approach to sequential decision...
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08/01/2011
