Pablo Hernandez-Leal

CoRR, 2021

2020

CDT: Cascading Decision Trees for Explainable Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Work in Progress: Temporally Extended Auxiliary Tasks.

[BibT_eX]

[DOI]

CoRR, 2020

Safe reinforcement learning using risk mapping by similarity.

[BibT_eX]

[DOI]

Jonathan Serrano Cuevas

Eduardo F. Morales

Adapt. Behav., 2020

A Very Condensed Survey and Critique of Multiagent Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Uncertainty-Aware Action Advising for Deep Reinforcement Learning Agents.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Providing Uncertainty-Based Advice for Deep Reinforcement Learning Agents (Student Abstract).

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Skynet: A Top Deep RL Agent in the Inaugural Pommerman Team Competition.

[BibT_eX]

[DOI]

CoRR, 2019

Safer Deep RL with Shallow MCTS: A Case Study in Pommerman.

[BibT_eX]

[DOI]

CoRR, 2019

A survey and critique of multiagent deep reinforcement learning.

[BibT_eX]

[DOI]

Auton. Agents Multi Agent Syst., 2019

Towers of Saliency: A Reinforcement Learning Visualization Using Immersive Environments.

[BibT_eX]

[DOI]

Proceedings of the 2019 ACM International Conference on Interactive Surfaces and Spaces, 2019

An Exchange Mechanism to Coordinate Flexibility in Residential Energy Cooperatives.

[BibT_eX]

[DOI]

Shantanu Chakraborty

Proceedings of the IEEE International Conference on Industrial Technology, 2019

Action Guidance with MCTS for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Fifteenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2019

Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Fifteenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2019

Agent Modeling as Auxiliary Task for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Fifteenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2019

On Hard Exploration for Reinforcement Learning: A Case Study in Pommerman.

[BibT_eX]

[DOI]

Proceedings of the Fifteenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2019

2018

Using Monte Carlo Tree Search as a Demonstrator within Asynchronous Deep RL.

[BibT_eX]

[DOI]

CoRR, 2018

Is multiagent deep reinforcement learning the answer or the question? A brief survey.

[BibT_eX]

[DOI]

CoRR, 2018

Load Classification and Forecasting for Temporary Power Installations.

[BibT_eX]

[DOI]

Arzam Muzaffar Kotriwala

Proceedings of the 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe, 2018

Coordinating Distributed and Flexible Resources: A Case-study of Residential Cooperatives.

[BibT_eX]

[DOI]

Shantanu Chakraborty

Proceedings of the 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe, 2018

2017

A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity.

[BibT_eX]

[DOI]

Tim Baarslag

CoRR, 2017

An exploration strategy for non-stationary opponents.

[BibT_eX]

[DOI]

Auton. Agents Multi Agent Syst., 2017

Efficiently detecting switches against non-stationary opponents.

[BibT_eX]

[DOI]

Auton. Agents Multi Agent Syst., 2017

An Exploration Strategy Facing Non-Stationary Agents.

[BibT_eX]

[DOI]

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Detecting Switches Against Non-Stationary Opponents.

[BibT_eX]

[DOI]

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Towards a Fast Detection of Opponents in Repeated Stochastic Games.

[BibT_eX]

[DOI]

Proceedings of the Autonomous Agents and Multiagent Systems, 2017

2016

Stress modelling and prediction in presence of scarce data.

[BibT_eX]

[DOI]

J. Biomed. Informatics, 2016

A Bayesian Approach for Learning and Tracking Switching, Non-Stationary Opponents: (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

Identifying and Tracking Switching, Non-Stationary Opponents: A Bayesian Approach.

[BibT_eX]

[DOI]

Proceedings of the Multiagent Interaction without Prior Coordination, 2016

2015

Bidding in Non-Stationary Energy Markets.

[BibT_eX]

[DOI]

Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 2015

Opponent Modeling against Non-stationary Strategies: (Doctoral Consortium).

[BibT_eX]

[DOI]

Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 2015

Stress Modelling Using Transfer Learning in Presence of Scarce Data.

[BibT_eX]

[DOI]

Proceedings of the Ambient Intelligence for Health - First International Conference, 2015

2014

Multi-label classification with Bayesian network-based chain classifiers.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2014

A framework for learning and planning against switching strategies in repeated games.

[BibT_eX]

[DOI]

Connect. Sci., 2014

Using a Priori Information for Fast Learning Against Non-stationary Opponents.

[BibT_eX]

[DOI]

Proceedings of the Advances in Artificial Intelligence - IBERAMIA 2014, 2014

2013

InstanceRank based on borders for instance selection.

[BibT_eX]

[DOI]

Jesús Ariel Carrasco-Ochoa

José Francisco Martínez Trinidad

José Arturo Olvera-López

Pattern Recognit., 2013

Learning temporal nodes Bayesian networks.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2013

Discovering human immunodeficiency virus mutational pathways using temporal Bayesian networks.

[BibT_eX]

[DOI]

Lindsey Jennifer Fiedler-Cameras

Felipe Orihuela-Espina

Eduardo F. Morales

Artif. Intell. Medicine, 2013

Strategic Interactions Among Agents with Bounded Rationality.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2013, 2013

Modeling non-stationary opponents.

[BibT_eX]

[DOI]

Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2013

2012

Contrasting Temporal Bayesian Network Models for Analyzing HIV Mutations.

[BibT_eX]

[DOI]

Lindsey Jennifer Fiedler-Cameras

Alma Rios-Flores

Jesus A. Gonzalez

Proceedings of the Ninth UAI Bayesian Modeling Applications Workshop, 2012

2011

Learning Temporal Bayesian Networks for Power Plant Diagnosis.

[BibT_eX]

[DOI]

Pablo H. Ibargüengoytia

Proceedings of the Modern Approaches in Applied Intelligence, 2011

Learning Temporal Nodes Bayesian Networks.

[BibT_eX]

[DOI]