Guandan × GameBot
CAG
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Challenge
Guandan, a partnership-based climbing card game with high strategic depth, faced challenges with matchmaking speed, rigid bot behavior, and a steep learning curve for newcomers.
Solution
GameBot introduced adaptive bots powered by our scalable reinforcement learning (RL) framework to improve both matchmaking efficiency and onboarding experience for new players.
Difficulty Scaling:
Bots trained across multiple skill tiers—from beginner-friendly to expert—allowing players to face appropriately challenging opponents while ensuring fair, balanced matches. This also enabled new players to learn partnership strategies progressively.
Seamless Matchmaking:
Bots automatically filled empty seats in real time, drastically reducing wait times and keeping games flowing smoothly. This ensured a consistent, satisfying gameplay experience for all participants.
Tactical Adaptability:
Bots dynamically adjust their strategies based on their partner’s actions, card distributions, and in-game developments, creating a more human-like, collaborative experience.
Impact
AI Win Rate: up to 61% in mid- to high-level matches, with a 31% win rate specifically in double-up situations.