129: Reinforcing Worldbuilding through Gameplay with Spoils
Dec 23, 2023
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Guests Daria Radu, Ben Wilson, and Douglas Wilson discuss the trick-taking card game Spoils and its development process. Topics include drawing inspiration from worldbuilding, trick-taking as a mechanic, the programming of AI systems, and the unique aspects of Spoils like point values and hoarding.
The AI in Spoils was designed to create a casual and enjoyable experience for players through friendly and non-threatening gameplay.
The variants in Spoils were designed to enhance the world-building aspect of the game by reflecting the cultures and stories of different islands.
The AI system in Spoils aimed to replicate the banter and interaction of real-life trick-taking card games, adding to the immersive single-player experience.
Deep dives
The Design of Spoils: AI and Gameplay
The AI in Spoils was designed to be a friendly and non-threatening opponent that could make mistakes, creating a casual and enjoyable experience for players. The AI system used deep reinforcement learning to train itself on the game, receiving rewards for winning tricks and playing good moves. Both opponent and partner AI were trained using the same system and received rewards for individual actions as well as teamwork. The bidding phase was more heuristic-based, as quantifying the goodness or badness of a chosen sweeper was challenging. The AI training process allowed for the discovery of interesting strategies and provided feedback on the design of the game.
Variants: Integrating Story and Gameplay
The variants in Spoils were designed to reflect the cultures and stories of different islands in the game. The rules of each variant were tailored to mirror the dynamics and conflicts of the respective islands. Variant rules like dueling sweepers and eruption eights added an extra layer of complexity and strategic depth, enhancing the world-building aspect of the game. The inclusion of these variants aimed to capture the essence of different fictional cultures and align the gameplay with the ongoing narrative of the game.
Reinforcing the Story: AI and World-Building
The AI system in Spoils aimed to replicate the banter and interaction that occurs in real-life trick-taking card games. The AI partners were designed to make mistakes and exhibit realistic gameplay, ensuring players felt they were having an authentic multiplayer experience. The inclusion of character barks added to the immersion and reflected cultural nuances of the archipelago. The use of deep reinforcement learning in the AI training process helped create an engaging and enjoyable single-player experience that reinforced the storytelling and cultural elements of the game.
The importance of strategic card play in the AI's training
During the training of the AI in a game, one of the challenges was teaching it how to strategically handle the Jack card, which is worth 11 points and can impact the outcome of the game. The AI primarily focused on winning the game, while humans also consider the importance of individual tricks. This was addressed by providing the AI with smaller rewards after each trick, allowing it to learn the consequences of its decision in real-time.
The value of unknown variables in gameplay
The podcast episode discusses how the AI in the game Spoils was deliberately not given access to all the information about the opponents' cards, simulating the experience of a human player. This created uncertainty and strategic complexity, as the AI had to make decisions without complete knowledge of its opponents' hands. This aspect of the game mirrored real-life human gameplay, where unknown variables and hidden information contribute to the strategic nature of the game.
Daria Radu, Ben Wilson, and our very own Douglas Wilson join us to discuss their trick-taking card game Spoils, featured as an optional game within story-driven adventure game Saltsea Chronicles. We discuss the genesis of the game, drawing inspiration from worldbuilding, trick-taking as a mechanic, the programming of the AI systems, and more.