Towards a Model of Puzznic
This work addresses a specific puzzle-solving problem for video game enthusiasts or AI researchers, but it is incremental as it builds on existing methods without major breakthroughs.
The authors tackled the problem of modeling and solving Puzznic, a video game involving planning moves to clear a grid by matching blocks, specifically for levels without moving blocks. They compared a planning approach with three constraint programming approaches on a small benchmark set, finding the planning approach superior but proposing improvements for the constraint models.
We report on progress in modelling and solving Puzznic, a video game requiring the player to plan sequences of moves to clear a grid by matching blocks. We focus here on levels with no moving blocks. We compare a planning approach and three constraint programming approaches on a small set of benchmark instances. The planning approach is at present superior to the constraint programming approaches, but we outline proposals for improving the constraint models.