no code implementations • 2 Mar 2023 • David Sychrovsky, Michal Sustr, Elnaz Davoodi, Marc Lanctot, Martin Schmid
To scale to games that cannot fit in memory, we can use search with value functions.
no code implementations • 2 Nov 2022 • Aleksandra Kalinowska, Elnaz Davoodi, Florian Strub, Kory W Mathewson, Ivana Kajic, Michael Bowling, Todd D Murphey, Patrick M Pilarski
While it is known that communication facilitates cooperation in multi-agent settings, it is unclear how to design artificial agents that can learn to effectively and efficiently communicate with each other.
no code implementations • 24 May 2022 • Aishwarya Agrawal, Ivana Kajić, Emanuele Bugliarello, Elnaz Davoodi, Anita Gergely, Phil Blunsom, Aida Nematzadeh
Vision-and-language (V&L) models pretrained on large-scale multimodal data have demonstrated strong performance on various tasks such as image captioning and visual question answering (VQA).
no code implementations • 17 Mar 2022 • Patrick M. Pilarski, Andrew Butcher, Elnaz Davoodi, Michael Bradley Johanson, Dylan J. A. Brenneis, Adam S. R. Parker, Leslie Acker, Matthew M. Botvinick, Joseph Modayil, Adam White
Our results showcase the speed of learning for Pavlovian signalling, the impact that different temporal representations do (and do not) have on agent-agent coordination, and how temporal aliasing impacts agent-agent and human-agent interactions differently.
no code implementations • 11 Jan 2022 • Andrew Butcher, Michael Bradley Johanson, Elnaz Davoodi, Dylan J. A. Brenneis, Leslie Acker, Adam S. R. Parker, Adam White, Joseph Modayil, Patrick M. Pilarski
We further show how to computationally build this adaptive signalling process out of a fixed signalling process, characterized by fast continual prediction learning and minimal constraints on the nature of the agent receiving signals.
no code implementations • 14 Dec 2021 • Dylan J. A. Brenneis, Adam S. Parker, Michael Bradley Johanson, Andrew Butcher, Elnaz Davoodi, Leslie Acker, Matthew M. Botvinick, Joseph Modayil, Adam White, Patrick M. Pilarski
Additionally, we compare two different agent architectures to assess how representational choices in agent design affect the human-agent interaction.
no code implementations • 6 Dec 2021 • Martin Schmid, Matej Moravcik, Neil Burch, Rudolf Kadlec, Josh Davidson, Kevin Waugh, Nolan Bard, Finbarr Timbers, Marc Lanctot, Zach Holland, Elnaz Davoodi, Alden Christianson, Michael Bowling
Games have a long history of serving as a benchmark for progress in artificial intelligence.
1 code implementation • ICLR 2022 • Rahma Chaabouni, Florian Strub, Florent Altché, Eugene Tarassov, Corentin Tallec, Elnaz Davoodi, Kory Wallace Mathewson, Olivier Tieleman, Angeliki Lazaridou, Bilal Piot
Emergent communication aims for a better understanding of human language evolution and building more efficient representations.
2 code implementations • 11 Jan 2021 • Samuel Sokota, Edward Lockhart, Finbarr Timbers, Elnaz Davoodi, Ryan D'Orazio, Neil Burch, Martin Schmid, Michael Bowling, Marc Lanctot
While this choice precludes CAPI from scaling to games as large as Hanabi, empirical results demonstrate that, on the games to which CAPI does scale, it is capable of discovering optimal joint policies even when other modern multi-agent reinforcement learning algorithms are unable to do so.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • WS 2018 • Charese Smiley, Elnaz Davoodi, Dezhao Song, Frank Schilder
This paper presents the two systems we entered into the 2017 E2E NLG Challenge: TemplGen, a templated-based system and SeqGen, a neural network-based system.
no code implementations • SEMEVAL 2016 • Elnaz Davoodi, Leila Kosseim
This paper describes the system deployed by the CLaC-EDLK team to the "SemEval 2016, Complex Word Identification task".
no code implementations • 19 Aug 2017 • Elnaz Davoodi, Leila Kosseim
This paper describes our approach to the 2016 QATS quality assessment shared task.
no code implementations • WS 2016 • Elnaz Davoodi, Leila Kosseim
This paper investigates the influence of discourse features on text complexity assessment.
1 code implementation • CONLL 2015 • Majid Laali, Elnaz Davoodi, Leila Kosseim
This paper describes our submission (kosseim15) to the CoNLL-2015 shared task on shallow discourse parsing.
no code implementations • RANLP 2017 • Elnaz Davoodi, Leila Kosseim
The automatic identification of discourse relations is still a challenging task in natural language processing.