AIIDE
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Official account of the AAAI conference on Artificial Intelligence and Interactive Digital Entertainment
With this we are all caught up! Stay tuned for the 2025 best paper award in November!
October 27, 2025 at 6:48 PM
With this we are all caught up! Stay tuned for the 2025 best paper award in November!
Reposted by AIIDE
🏆 Best Paper – 2024
Generalized Entropy and Solution Information for Measuring Puzzle Difficulty by Shen and Sturtevant
Puzzle entropy uses information entropy with respect to player knowledge to measure the difficulty of a puzzle. The paper generalizes and refines this idea.
Generalized Entropy and Solution Information for Measuring Puzzle Difficulty by Shen and Sturtevant
Puzzle entropy uses information entropy with respect to player knowledge to measure the difficulty of a puzzle. The paper generalizes and refines this idea.
October 27, 2025 at 6:46 PM
🏆 Best Paper – 2024
Generalized Entropy and Solution Information for Measuring Puzzle Difficulty by Shen and Sturtevant
Puzzle entropy uses information entropy with respect to player knowledge to measure the difficulty of a puzzle. The paper generalizes and refines this idea.
Generalized Entropy and Solution Information for Measuring Puzzle Difficulty by Shen and Sturtevant
Puzzle entropy uses information entropy with respect to player knowledge to measure the difficulty of a puzzle. The paper generalizes and refines this idea.
🏆 Best Paper – 2024
Generalized Entropy and Solution Information for Measuring Puzzle Difficulty by Shen and Sturtevant
Puzzle entropy uses information entropy with respect to player knowledge to measure the difficulty of a puzzle. The paper generalizes and refines this idea.
Generalized Entropy and Solution Information for Measuring Puzzle Difficulty by Shen and Sturtevant
Puzzle entropy uses information entropy with respect to player knowledge to measure the difficulty of a puzzle. The paper generalizes and refines this idea.
October 27, 2025 at 6:46 PM
🏆 Best Paper – 2024
Generalized Entropy and Solution Information for Measuring Puzzle Difficulty by Shen and Sturtevant
Puzzle entropy uses information entropy with respect to player knowledge to measure the difficulty of a puzzle. The paper generalizes and refines this idea.
Generalized Entropy and Solution Information for Measuring Puzzle Difficulty by Shen and Sturtevant
Puzzle entropy uses information entropy with respect to player knowledge to measure the difficulty of a puzzle. The paper generalizes and refines this idea.
Reposted by AIIDE
🏆 Best Paper – 2023
There and Back Again: Extracting Formal Domains for Controllable Neurosymbolic Story Authoring by Kelly et al.
Language models create fluent narratives, while planning-based story generators offer control. This paper explores how to combine the best of both!
There and Back Again: Extracting Formal Domains for Controllable Neurosymbolic Story Authoring by Kelly et al.
Language models create fluent narratives, while planning-based story generators offer control. This paper explores how to combine the best of both!
October 21, 2025 at 10:24 PM
🏆 Best Paper – 2023
There and Back Again: Extracting Formal Domains for Controllable Neurosymbolic Story Authoring by Kelly et al.
Language models create fluent narratives, while planning-based story generators offer control. This paper explores how to combine the best of both!
There and Back Again: Extracting Formal Domains for Controllable Neurosymbolic Story Authoring by Kelly et al.
Language models create fluent narratives, while planning-based story generators offer control. This paper explores how to combine the best of both!
🏆 Best Paper – 2023
There and Back Again: Extracting Formal Domains for Controllable Neurosymbolic Story Authoring by Kelly et al.
Language models create fluent narratives, while planning-based story generators offer control. This paper explores how to combine the best of both!
There and Back Again: Extracting Formal Domains for Controllable Neurosymbolic Story Authoring by Kelly et al.
Language models create fluent narratives, while planning-based story generators offer control. This paper explores how to combine the best of both!
October 21, 2025 at 10:24 PM
🏆 Best Paper – 2023
There and Back Again: Extracting Formal Domains for Controllable Neurosymbolic Story Authoring by Kelly et al.
Language models create fluent narratives, while planning-based story generators offer control. This paper explores how to combine the best of both!
There and Back Again: Extracting Formal Domains for Controllable Neurosymbolic Story Authoring by Kelly et al.
Language models create fluent narratives, while planning-based story generators offer control. This paper explores how to combine the best of both!
Reposted by AIIDE
🏆 Best Paper – 2022
Puck: A Slow and Personal Automated Game Designer by Michael Cook
The author outlines new goals for automated game design focused on users and communities. The result is Puck, an automated game design system with an exhaustive approach to content generation.
Puck: A Slow and Personal Automated Game Designer by Michael Cook
The author outlines new goals for automated game design focused on users and communities. The result is Puck, an automated game design system with an exhaustive approach to content generation.
October 21, 2025 at 10:23 PM
🏆 Best Paper – 2022
Puck: A Slow and Personal Automated Game Designer by Michael Cook
The author outlines new goals for automated game design focused on users and communities. The result is Puck, an automated game design system with an exhaustive approach to content generation.
Puck: A Slow and Personal Automated Game Designer by Michael Cook
The author outlines new goals for automated game design focused on users and communities. The result is Puck, an automated game design system with an exhaustive approach to content generation.
🏆 Best Paper – 2022
Puck: A Slow and Personal Automated Game Designer by Michael Cook
The author outlines new goals for automated game design focused on users and communities. The result is Puck, an automated game design system with an exhaustive approach to content generation.
Puck: A Slow and Personal Automated Game Designer by Michael Cook
The author outlines new goals for automated game design focused on users and communities. The result is Puck, an automated game design system with an exhaustive approach to content generation.
October 21, 2025 at 10:23 PM
🏆 Best Paper – 2022
Puck: A Slow and Personal Automated Game Designer by Michael Cook
The author outlines new goals for automated game design focused on users and communities. The result is Puck, an automated game design system with an exhaustive approach to content generation.
Puck: A Slow and Personal Automated Game Designer by Michael Cook
The author outlines new goals for automated game design focused on users and communities. The result is Puck, an automated game design system with an exhaustive approach to content generation.
Reposted by AIIDE
🏆 Best Paper – 2021
MappyLand: Fast, Accurate Mapping for Console Games by Osborn et al.
Game maps are useful for humans, game-playing agents, and content generation. Mappyland uses a variety of heuristics and algorithms to automatically generate accurate maps from example play.
MappyLand: Fast, Accurate Mapping for Console Games by Osborn et al.
Game maps are useful for humans, game-playing agents, and content generation. Mappyland uses a variety of heuristics and algorithms to automatically generate accurate maps from example play.
October 12, 2025 at 12:34 AM
🏆 Best Paper – 2021
MappyLand: Fast, Accurate Mapping for Console Games by Osborn et al.
Game maps are useful for humans, game-playing agents, and content generation. Mappyland uses a variety of heuristics and algorithms to automatically generate accurate maps from example play.
MappyLand: Fast, Accurate Mapping for Console Games by Osborn et al.
Game maps are useful for humans, game-playing agents, and content generation. Mappyland uses a variety of heuristics and algorithms to automatically generate accurate maps from example play.
🏆 Best Paper – 2021
MappyLand: Fast, Accurate Mapping for Console Games by Osborn et al.
Game maps are useful for humans, game-playing agents, and content generation. Mappyland uses a variety of heuristics and algorithms to automatically generate accurate maps from example play.
MappyLand: Fast, Accurate Mapping for Console Games by Osborn et al.
Game maps are useful for humans, game-playing agents, and content generation. Mappyland uses a variety of heuristics and algorithms to automatically generate accurate maps from example play.
October 12, 2025 at 12:34 AM
🏆 Best Paper – 2021
MappyLand: Fast, Accurate Mapping for Console Games by Osborn et al.
Game maps are useful for humans, game-playing agents, and content generation. Mappyland uses a variety of heuristics and algorithms to automatically generate accurate maps from example play.
MappyLand: Fast, Accurate Mapping for Console Games by Osborn et al.
Game maps are useful for humans, game-playing agents, and content generation. Mappyland uses a variety of heuristics and algorithms to automatically generate accurate maps from example play.
Find their bios and the keynote abstract here:
🔗 sites.google.com/ualberta.ca/...
And make sure to register for AIIDE here:
🔗 sites.google.com/ualberta.ca/...
🔗 sites.google.com/ualberta.ca/...
And make sure to register for AIIDE here:
🔗 sites.google.com/ualberta.ca/...
AIIDE 2025 - Keynote Speakers
sites.google.com
October 6, 2025 at 8:25 PM
Find their bios and the keynote abstract here:
🔗 sites.google.com/ualberta.ca/...
And make sure to register for AIIDE here:
🔗 sites.google.com/ualberta.ca/...
🔗 sites.google.com/ualberta.ca/...
And make sure to register for AIIDE here:
🔗 sites.google.com/ualberta.ca/...
Reposted by AIIDE
🏆 Best Paper – 2020
“It’s Unwieldy and It Takes a Lot of Time” —Challenges and Opportunities for Creating Agents in Commercial Games by Jacob et al.
Game research should consider industry best practices; this paper interviews creators to identify challenges in making AI agents.
“It’s Unwieldy and It Takes a Lot of Time” —Challenges and Opportunities for Creating Agents in Commercial Games by Jacob et al.
Game research should consider industry best practices; this paper interviews creators to identify challenges in making AI agents.
September 29, 2025 at 6:23 PM
🏆 Best Paper – 2020
“It’s Unwieldy and It Takes a Lot of Time” —Challenges and Opportunities for Creating Agents in Commercial Games by Jacob et al.
Game research should consider industry best practices; this paper interviews creators to identify challenges in making AI agents.
“It’s Unwieldy and It Takes a Lot of Time” —Challenges and Opportunities for Creating Agents in Commercial Games by Jacob et al.
Game research should consider industry best practices; this paper interviews creators to identify challenges in making AI agents.
🏆 Best Paper – 2020
“It’s Unwieldy and It Takes a Lot of Time” —Challenges and Opportunities for Creating Agents in Commercial Games by Jacob et al.
Game research should consider industry best practices; this paper interviews creators to identify challenges in making AI agents.
“It’s Unwieldy and It Takes a Lot of Time” —Challenges and Opportunities for Creating Agents in Commercial Games by Jacob et al.
Game research should consider industry best practices; this paper interviews creators to identify challenges in making AI agents.
September 29, 2025 at 6:23 PM
🏆 Best Paper – 2020
“It’s Unwieldy and It Takes a Lot of Time” —Challenges and Opportunities for Creating Agents in Commercial Games by Jacob et al.
Game research should consider industry best practices; this paper interviews creators to identify challenges in making AI agents.
“It’s Unwieldy and It Takes a Lot of Time” —Challenges and Opportunities for Creating Agents in Commercial Games by Jacob et al.
Game research should consider industry best practices; this paper interviews creators to identify challenges in making AI agents.
Reposted by AIIDE
🏆 Best Paper – 2019
Macro Action Selection with Deep Reinforcement Learning in StarCraft by Xu et al.
To reduce the gap between human players and StarCraft bots, Xu et al. propose using a Deep Reinforcement Learning framework to select macro actions instead of predefined rules.
Macro Action Selection with Deep Reinforcement Learning in StarCraft by Xu et al.
To reduce the gap between human players and StarCraft bots, Xu et al. propose using a Deep Reinforcement Learning framework to select macro actions instead of predefined rules.
September 23, 2025 at 9:20 PM
🏆 Best Paper – 2019
Macro Action Selection with Deep Reinforcement Learning in StarCraft by Xu et al.
To reduce the gap between human players and StarCraft bots, Xu et al. propose using a Deep Reinforcement Learning framework to select macro actions instead of predefined rules.
Macro Action Selection with Deep Reinforcement Learning in StarCraft by Xu et al.
To reduce the gap between human players and StarCraft bots, Xu et al. propose using a Deep Reinforcement Learning framework to select macro actions instead of predefined rules.
🏆 Best Paper – 2019
Macro Action Selection with Deep Reinforcement Learning in StarCraft by Xu et al.
To reduce the gap between human players and StarCraft bots, Xu et al. propose using a Deep Reinforcement Learning framework to select macro actions instead of predefined rules.
Macro Action Selection with Deep Reinforcement Learning in StarCraft by Xu et al.
To reduce the gap between human players and StarCraft bots, Xu et al. propose using a Deep Reinforcement Learning framework to select macro actions instead of predefined rules.
September 23, 2025 at 9:20 PM
🏆 Best Paper – 2019
Macro Action Selection with Deep Reinforcement Learning in StarCraft by Xu et al.
To reduce the gap between human players and StarCraft bots, Xu et al. propose using a Deep Reinforcement Learning framework to select macro actions instead of predefined rules.
Macro Action Selection with Deep Reinforcement Learning in StarCraft by Xu et al.
To reduce the gap between human players and StarCraft bots, Xu et al. propose using a Deep Reinforcement Learning framework to select macro actions instead of predefined rules.