no code implementations • 17 Jan 2023 • Lakshita Dodeja, Pradyumna Tambwekar, Erin Hedlund-Botti, Matthew Gombolay
While these strategy recommendation schemes have been explored independently in prior work, our study is novel in that we employ all of them simultaneously and in the context of strategy recommendations, to provide us an in-depth overview of the perception of different strategy recommendation systems.
no code implementations • 13 Jan 2023 • Pradyumna Tambwekar, Matthew Gombolay
Our findings highlight internal consistency issues wherein participants perceived language explanations to be significantly more usable, however participants were better able to objectively understand the decision making process of the car through a decision tree explanation.
Decision Making Explainable Artificial Intelligence (XAI) +1
no code implementations • 7 Oct 2022 • Andrew Silva, Pradyumna Tambwekar, Matthew Gombolay
Federated learning is a training paradigm that learns from multiple distributed users without aggregating data on a centralized server.
1 code implementation • 17 Aug 2022 • Pradyumna Tambwekar, Lakshita Dodeja, Nathan Vaska, Wei Xu, Matthew Gombolay
Leveraging a game environment, we collect a dataset of over 1000 examples, mapping language strategies to the corresponding goals and constraints, and show that our model, trained on this dataset, significantly outperforms human interpreters in inferring strategic intent (i. e., goals and constraints) from language (p < 0. 05).
no code implementations • NAACL 2021 • Andrew Silva, Pradyumna Tambwekar, Matthew Gombolay
The ease of access to pre-trained transformers has enabled developers to leverage large-scale language models to build exciting applications for their users.
1 code implementation • 18 Jan 2021 • Pradyumna Tambwekar, Andrew Silva, Nakul Gopalan, Matthew Gombolay
Human-AI policy specification is a novel procedure we define in which humans can collaboratively warm-start a robot's reinforcement learning policy.
no code implementations • 11 Jan 2019 • Upol Ehsan, Pradyumna Tambwekar, Larry Chan, Brent Harrison, Mark Riedl
The second study further explores user preferences between the generated rationales with regard to confidence in the autonomous agent, communicating failure and unexpected behavior.
1 code implementation • 27 Sep 2018 • Pradyumna Tambwekar, Murtaza Dhuliawala, Lara J. Martin, Animesh Mehta, Brent Harrison, Mark O. Riedl
Language-modeling--based approaches to story plot generation attempt to construct a plot by sampling from a language model (LM) to predict the next character, word, or sentence to add to the story.