Christopher Amato

Orcid: 0000-0002-6786-7384

According to our database1, Christopher Amato authored at least 109 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Adversarial Inception for Bounded Backdoor Poisoning in Deep Reinforcement Learning.
CoRR, 2024

An Introduction to Centralized Training for Decentralized Execution in Cooperative Multi-Agent Reinforcement Learning.
CoRR, 2024

On Stateful Value Factorization in Multi-Agent Reinforcement Learning.
CoRR, 2024

SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents.
CoRR, 2024

(A Partial Survey of) Decentralized, Cooperative Multi-Agent Reinforcement Learning.
CoRR, 2024

Shield Decomposition for Safe Reinforcement Learning in General Partially Observable Multi-Agent Environments.
RLJ, 2024

Robot Navigation in Unseen Environments using Coarse Maps.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Shield Decentralization for Safe Reinforcement Learning in General Partially Observable Multi-Agent Environments.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Entropy Seeking Constrained Multiagent Reinforcement Learning.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023
On Centralized Critics in Multi-Agent Reinforcement Learning.
J. Artif. Intell. Res., 2023

Vision and Language Navigation in the Real World via Online Visual Language Mapping.
CoRR, 2023

Multi-Agent Reinforcement Learning Based on Representational Communication for Large-Scale Traffic Signal Control.
IEEE Access, 2023

On-Robot Bayesian Reinforcement Learning for POMDPs.
IROS, 2023

Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Improving Deep Policy Gradients with Value Function Search.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Equivariant Reinforcement Learning under Partial Observability.
Proceedings of the Conference on Robot Learning, 2023

Safe Deep Reinforcement Learning by Verifying Task-Level Properties.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022
Deep Transformer Q-Networks for Partially Observable Reinforcement Learning.
CoRR, 2022

Hierarchical Reinforcement Learning Under Mixed Observability.
Proceedings of the Algorithmic Foundations of Robotics XV, 2022

Asymmetric DQN for partially observable reinforcement learning.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Shield Decentralization for Safe Multi-Agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Safety-informed mutations for evolutionary deep reinforcement learning.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Leveraging Fully Observable Policies for Learning under Partial Observability.
Proceedings of the Conference on Robot Learning, 2022

BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Unbiased Asymmetric Reinforcement Learning under Partial Observability.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

A Deeper Understanding of State-Based Critics in Multi-Agent Reinforcement Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Improving the Efficiency of Off-Policy Reinforcement Learning by Accounting for Past Decisions.
CoRR, 2021

Virtual Replay Cache.
CoRR, 2021

Human-Level Control without Server-Grade Hardware.
CoRR, 2021

Investigating Alternatives to the Root Mean Square for Adaptive Gradient Methods.
CoRR, 2021

Unbiased Asymmetric Actor-Critic for Partially Observable Reinforcement Learning.
CoRR, 2021

End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning.
CoRR, 2021

Decentralized Reinforcement Learning for Multi-Target Search and Detection by a Team of Drones.
CoRR, 2021

Multi-agent reinforcement learning with directed exploration and selective memory reuse.
Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021

Local Advantage Actor-Critic for Robust Multi-Agent Deep Reinforcement Learning.
Proceedings of the International Symposium on Multi-Robot and Multi-Agent Systems, 2021

Reconciling Rewards with Predictive State Representations.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning<sup>*</sup>.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Contrasting Centralized and Decentralized Critics in Multi-Agent Reinforcement Learning.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

Safe Multi-Agent Reinforcement Learning via Shielding.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

Stratified Experience Replay: Correcting Multiplicity Bias in Off-Policy Reinforcement Learning.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020
Special Issue on the 2018 Robotics: Science and Systems Conference.
Int. J. Robotics Res., 2020

Expectigrad: Fast Stochastic Optimization with Robust Convergence Properties.
CoRR, 2020

To Ask or Not to Ask: A User Annoyance Aware Preference Elicitation Framework for Social Robots.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Learning Multi-Robot Decentralized Macro-Action-Based Policies via a Centralized Q-Net.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Hybrid Independent Learning in Cooperative Markov Games.
Proceedings of the Distributed Artificial Intelligence - Second International Conference, 2020

Hierarchical Robot Navigation in Novel Environments using Rough 2-D Maps.
Proceedings of the 4th Conference on Robot Learning, 2020

Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability.
Proceedings of the 4th Conference on Robot Learning, 2020

Towards End-to-End Control of a Robot Prosthetic Hand via Reinforcement Learning.
Proceedings of the 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2020

Likelihood Quantile Networks for Coordinating Multi-Agent Reinforcement Learning.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Learning Complementary Representations of the Past using Auxiliary Tasks in Partially Observable Reinforcement Learning.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Multi-Agent/Robot Deep Reinforcement Learning with Macro-Actions (Student Abstract).
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Modeling and Planning with Macro-Actions in Decentralized POMDPs.
J. Artif. Intell. Res., 2019

Active Goal Recognition.
CoRR, 2019

Multi-Robot Deep Reinforcement Learning with Macro-Actions.
CoRR, 2019

AAAI/ACM SIGAI job fair 2019: a retrospective.
AI Matters, 2019

Reconciling λ-Returns with Experience Replay.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Online Planning for Target Object Search in Clutter under Partial Observability.
Proceedings of the International Conference on Robotics and Automation, 2019

Macro-Action-Based Deep Multi-Agent Reinforcement Learning.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Bayesian RL in Factored POMDPs.
Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

Bayesian Reinforcement Learning in Factored POMDPs.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Learning to Teach in Cooperative Multiagent Reinforcement Learning.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
On Improving Decentralized Hysteretic Deep Reinforcement Learning.
CoRR, 2018

Efficient Eligibility Traces for Deep Reinforcement Learning.
CoRR, 2018

Reports on the 2018 AAAI Spring Symposium Series.
AI Mag., 2018

The art of drafting: a team-oriented hero recommendation system for multiplayer online battle arena games.
Proceedings of the 12th ACM Conference on Recommender Systems, 2018

Decision-Making Under Uncertainty in Multi-Agent and Multi-Robot Systems: Planning and Learning.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Q-DeckRec: A Fast Deck Recommendation System for Collectible Card Games.
Proceedings of the 2018 IEEE Conference on Computational Intelligence and Games, 2018

2017
Decentralized control of multi-robot partially observable Markov decision processes using belief space macro-actions.
Int. J. Robotics Res., 2017

Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions.
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

COG-DICE: An Algorithm for Solving Continuous-Observation Dec-POMDPs.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Scalable accelerated decentralized multi-robot policy search in continuous observation spaces.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability.
Proceedings of the 34th International Conference on Machine Learning, 2017

Learning in POMDPs with Monte Carlo Tree Search.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
A Concise Introduction to Decentralized POMDPs
Springer Briefs in Intelligent Systems, Springer, ISBN: 978-3-319-28929-8, 2016

Optimally Solving Dec-POMDPs as Continuous-State MDPs.
J. Artif. Intell. Res., 2016

Policy search for multi-robot coordination under uncertainty.
Int. J. Robotics Res., 2016

Reports of the AAAI 2016 Spring Symposium Series.
AI Mag., 2016

Graph-based Cross Entropy method for solving multi-robot decentralized POMDPs.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Learning for Decentralized Control of Multiagent Systems in Large, Partially-Observable Stochastic Environments.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Stick-Breaking Policy Learning in Dec-POMDPs.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Exploiting Separability in Multiagent Planning with Continuous-State MDPs (Extended Abstract).
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Decentralized control of Partially Observable Markov Decision Processes using belief space macro-actions.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Planning for decentralized control of multiple robots under uncertainty.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Probabilistic Planning for Decentralized Multi-Robot Systems.
Proceedings of the 2015 AAAI Fall Symposia, Arlington, Virginia, USA, November 12-14, 2015, 2015

Scalable Planning and Learning for Multiagent POMDPs.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Exploiting separability in multiagent planning with continuous-state MDPs.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

Planning with macro-actions in decentralized POMDPs.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

2013
Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs.
J. Artif. Intell. Res., 2013

Decentralized control of partially observable Markov decision processes.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Producing efficient error-bounded solutions for transition independent decentralized mdps.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2013

2012
Scaling Up Decentralized MDPs Through Heuristic Search.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Using POMDPs to Control an Accuracy-Processing Time Trade-Off in Video Surveillance.
Proceedings of the Twenty-Fourth Conference on Innovative Applications of Artificial Intelligence, 2012

2011
Scaling Up Optimal Heuristic Search in Dec-POMDPs via Incremental Expansion.
Proceedings of the IJCAI 2011, 2011

Decision Support in Organizations: A Case for OrgPOMDPs.
Proceedings of the 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2011

Adaptive decision support for structured organizations: a case for OrgPOMDPs.
Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), 2011

Decentralized Models for Use in a Real-World Personal Assistant Agent Scenario.
Proceedings of the Help Me Help You: Bridging the Gaps in Human-Agent Collaboration, 2011

2010
Optimizing fixed-size stochastic controllers for POMDPs and decentralized POMDPs.
Auton. Agents Multi Agent Syst., 2010

Heuristic search for identical payoff Bayesian games.
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010

High-level reinforcement learning in strategy games.
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010

Finite-State Controllers Based on Mealy Machines for Centralized and Decentralized POMDPs.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Policy Iteration for Decentralized Control of Markov Decision Processes.
J. Artif. Intell. Res., 2009

Achieving goals in decentralized POMDPs.
Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), 2009

Incremental Policy Generation for Finite-Horizon DEC-POMDPs.
Proceedings of the 19th International Conference on Automated Planning and Scheduling, 2009

2007
Optimizing Memory-Bounded Controllers for Decentralized POMDPs.
Proceedings of the UAI 2007, 2007

Solving POMDPs Using Quadratically Constrained Linear Programs.
Proceedings of the IJCAI 2007, 2007

2006
Finding Optimal POMDP Controllers Using Quadratically Constrained Linear Programs.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2006


  Loading...