‘Diplomacy AI’ directory
- See Also
-
Links
- “What If the Robots Were Very Nice While They Took Over the World?”, Heffernan 2023
- “Negotiation and Honesty in Artificial Intelligence Methods for the Board Game of Diplomacy”, Kramár et al 2022
- “CICERO: Human-Level Play in the Game of Diplomacy by Combining Language Models With Strategic Reasoning: Supplement”, Team et al 2022
- “CICERO: Human-Level Play in the Game of Diplomacy by Combining Language Models With Strategic Reasoning”, Bakhtin et al 2022
- “Diplodocus: Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning”, Bakhtin et al 2022
- “Modeling Strong and Human-Like Gameplay With KL-Regularized Search”, Jacob et al 2021
- “DORA: No-Press Diplomacy from Scratch”, Bakhtin et al 2021
- “Human-Level Performance in No-Press Diplomacy via Equilibrium Search”, Gray et al 2020
- “Learning to Play No-Press Diplomacy With Best Response Policy Iteration”, Anthony et al 2020
- “No Press Diplomacy: Modeling Multi-Agent Gameplay”, Paquette et al 2019
- “The Challenge of Negotiation in the Game of Diplomacy”, Jonge et al 2018
- “Diplomat, an Agent in a Multi Agent Environment: An Overview”, Kraus & Lehmann 1988
- “Hsdip: a Diplomacy Parser/renderer”
- Wikipedia
- Miscellaneous
- Bibliography
See Also
Links
“What If the Robots Were Very Nice While They Took Over the World?”, Heffernan 2023
What If the Robots Were Very Nice While They Took Over the World?
“Negotiation and Honesty in Artificial Intelligence Methods for the Board Game of Diplomacy”, Kramár et al 2022
Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy
“CICERO: Human-Level Play in the Game of Diplomacy by Combining Language Models With Strategic Reasoning: Supplement”, Team et al 2022
“CICERO: Human-Level Play in the Game of Diplomacy by Combining Language Models With Strategic Reasoning”, Bakhtin et al 2022
“Diplodocus: Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning”, Bakhtin et al 2022
“Modeling Strong and Human-Like Gameplay With KL-Regularized Search”, Jacob et al 2021
Modeling Strong and Human-Like Gameplay with KL-Regularized Search
“DORA: No-Press Diplomacy from Scratch”, Bakhtin et al 2021
“Human-Level Performance in No-Press Diplomacy via Equilibrium Search”, Gray et al 2020
Human-Level Performance in No-Press Diplomacy via Equilibrium Search
“Learning to Play No-Press Diplomacy With Best Response Policy Iteration”, Anthony et al 2020
Learning to Play No-Press Diplomacy with Best Response Policy Iteration
“No Press Diplomacy: Modeling Multi-Agent Gameplay”, Paquette et al 2019
“The Challenge of Negotiation in the Game of Diplomacy”, Jonge et al 2018
“Diplomat, an Agent in a Multi Agent Environment: An Overview”, Kraus & Lehmann 1988
Diplomat, an agent in a multi agent environment: An overview
“Hsdip: a Diplomacy Parser/renderer”
hsdip: a Diplomacy parser/renderer :
View External Link:
Wikipedia
Miscellaneous
Bibliography
-
https://www.nature.com/articles/s41467-022-34473-5#deepmind: “Negotiation and Honesty in Artificial Intelligence Methods for the Board Game of Diplomacy”, -
2022-bakhtin.pdf: “CICERO: Human-Level Play in the Game of Diplomacy by Combining Language Models With Strategic Reasoning”,