Improving Solvability for Procedurally Generated Challenges in Physical Solitaire Games Through Entangled Components
| Autor: | James Droscha, Mark Goadrich |
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| Rok vydání: | 2018 |
| Předmět: |
FOS: Computer and information sciences
Theoretical computer science Computer Science - Artificial Intelligence Computer science Monte Carlo method Computer Science - Human-Computer Interaction Approximation algorithm Game board Terminology Human-Computer Interaction (cs.HC) Artificial Intelligence (cs.AI) Artificial Intelligence Control and Systems Engineering Component (UML) Electrical and Electronic Engineering Control (linguistics) Software Randomness |
| DOI: | 10.48550/arxiv.1810.01926 |
| Popis: | Challenges for physical solitaire puzzle games are typically designed in advance by humans and limited in number. Alternatively, some games incorporate rules for stochastic setup, where the human solver randomly sets up the game board before solving the challenge. These setup rules greatly increase the number of possible challenges, but can often generate unsolvable or uninteresting challenges. To better understand the compromises involved in minimizing undesirable challenges, we examine three games where component design choices can influence the stochastic nature of the resulting challenge generation algorithms. We evaluate the effect of these components and algorithms on challenge solvability and challenge engagement. We find that algorithms which control randomness through entangling components based on sub-elements of the puzzle mechanics can generate interesting challenges with a high probability of being solvable. Comment: 10 pages, 19 figures. Accepted to IEEE Transactions on Games, Early Access 5/24/2019 |
| Databáze: | OpenAIRE |
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