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09/16/2023
Interactively Teaching an Inverse Reinforcement Learner with Limited Feedback
We study the problem of teaching via demonstrations in sequential decisi...
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01/10/2023
Learning to Perceive in Deep Model-Free Reinforcement Learning
This work proposes a novel model-free Reinforcement Learning (RL) agent ...
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10/12/2022
Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning
We introduce hybrid execution in multi-agent reinforcement learning (MAR...
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09/19/2022
"Guess what I'm doing": Extending legibility to sequential decision tasks
In this paper we investigate the notion of legibility in sequential deci...
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02/07/2022
GMC – Geometric Multimodal Contrastive Representation Learning
Learning representations of multimodal data that are both informative an...
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01/30/2022
Learning Collective Action under Risk Diversity
Collective risk dilemmas (CRDs) are a class of n-player games that repre...
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01/10/2022
Assisting Unknown Teammates in Unknown Tasks: Ad Hoc Teamwork under Partial Observability
In this paper, we present a novel Bayesian online prediction algorithm f...
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11/23/2021
Understanding the Impact of Data Distribution on Q-learning with Function Approximation
In this work, we focus our attention on the study of the interplay betwe...
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10/07/2021
How to Sense the World: Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning Agents
This work addresses the problem of sensing the world: how to learn a mul...
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06/29/2021
Limited depth bandit-based strategy for Monte Carlo planning in continuous action spaces
This paper addresses the problem of optimal control using search trees. ...
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01/24/2021
A Methodology for the Development of RL-Based Adaptive Traffic Signal Controllers
This article proposes a methodology for the development of adaptive traf...
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10/17/2020
A Game AI Competition to foster Collaborative AI research and development
Game AI competitions are important to foster research and development on...
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06/04/2020
MHVAE: a Human-Inspired Deep Hierarchical Generative Model for Multimodal Representation Learning
Humans are able to create rich representations of their external reality...
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11/28/2019
Playing Games in the Dark: An approach for cross-modality transfer in reinforcement learning
In this work we explore the use of latent representations obtained from ...
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09/22/2019
Multi-task Learning and Catastrophic Forgetting in Continual Reinforcement Learning
In this paper we investigate two hypothesis regarding the use of deep re...
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03/06/2019
Learning multimodal representations for sample-efficient recognition of human actions
Humans interact in rich and diverse ways with the environment. However, ...
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02/05/2019
Empathic Robot for Group Learning: A Field Study
This work explores a group learning scenario with an autonomous empathic...
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12/18/2018