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==A non-linear progression & semi-random trees== |
==A non-linear progression & semi-random trees== |
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| − | The randomness is designed to include a part of uncertainty, as, in the ancient history of humanity, did not have control about where the areas of knowledge were moving, for each node in each horizontal row in each one area is randomized, the nodes revealed when you acquire an adjacent tech |
+ | The randomness is designed to include a part of uncertainty, as, in the ancient history of humanity, did not have control about where the areas of knowledge were moving, for each node in each horizontal row in each one area is randomized, the nodes revealed when you acquire an adjacent tech, the max-combination possible for each row is '''16 (4x4)''' guaranteeing low uncertainty along all path. |
Revision as of 06:39, 16 June 2019
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Knowledge tree or "Tech tree", togueder with the Historical progression forms the Progression system in BOCProject. The Knowledge tree can reach the tech/knowledge victory.
Mechanics
The pre-alpha knowledge tree has 256 nodes, divided into the different 8 progression points as areas, the player unlocking nodes based in the progression incomings points for each turn for each different areas. for example, If the player gets 10 military points in one turn, their progression on military area grows 10 points. The player progress over different areas at the same time based on incoming points of each area.
Omnidirectional tree progression system
The knowledge tree is a omnidirectional progression system, the player progress over different areas based on the incoming points for each one at the same time.
A non-linear progression & semi-random trees
The randomness is designed to include a part of uncertainty, as, in the ancient history of humanity, did not have control about where the areas of knowledge were moving, for each node in each horizontal row in each one area is randomized, the nodes revealed when you acquire an adjacent tech, the max-combination possible for each row is 16 (4x4) guaranteeing low uncertainty along all path.