Melinda T. Gervasio

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with Pedro Sequeira

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Publications

2023
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Pedro Sequeira, Melinda T. Gervasio:
IxDRL: A Novel Explainable Deep Reinforcement Learning Toolkit Based on Analyses of Interestingness. xAI (1) 2023: 373-396
[c29]
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Eric Yeh, Pedro Sequeira, Jesse Hostetler, Melinda T. Gervasio:
Outcome-Guided Counterfactuals from a Jointly Trained Generative Latent Space. xAI (3) 2023: 449-469
[i7]
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  - journals/corr/abs-2307-08933
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Pedro Sequeira, Melinda T. Gervasio:
IxDRL: A Novel Explainable Deep Reinforcement Learning Toolkit based on Analyses of Interestingness. CoRR abs/2307.08933 (2023)
2022
[i5]
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  - journals/corr/abs-2207-07710
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Eric Yeh, Pedro Sequeira, Jesse Hostetler, Melinda T. Gervasio:
Outcome-Guided Counterfactuals for Reinforcement Learning Agents from a Jointly Trained Generative Latent Space. CoRR abs/2207.07710 (2022)
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  - journals/corr/abs-2208-08552
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Pedro Sequeira, Daniel Elenius, Jesse Hostetler, Melinda T. Gervasio:
A Framework for Understanding and Visualizing Strategies of RL Agents. CoRR abs/2208.08552 (2022)
[i3]
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  - journals/corr/abs-2211-06376
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Pedro Sequeira, Jesse Hostetler, Melinda T. Gervasio:
Global and Local Analysis of Interestingness for Competency-Aware Deep Reinforcement Learning. CoRR abs/2211.06376 (2022)
2020
[j6]
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Pedro Sequeira, Melinda T. Gervasio:
Interestingness elements for explainable reinforcement learning: Understanding agents' capabilities and limitations. Artif. Intell. 288: 103367 (2020)
2019
[c27]
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Pedro Sequeira, Eric Yeh, Melinda T. Gervasio:
Interestingness Elements for Explainable Reinforcement Learning through Introspection. IUI Workshops 2019
[i1]
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  - journals/corr/abs-1912-09007
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Pedro Sequeira, Melinda T. Gervasio:
Interestingness Elements for Explainable Reinforcement Learning: Understanding Agents' Capabilities and Limitations. CoRR abs/1912.09007 (2019)

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