January 31, 2019
Thesis – Generative System for Physics Based Games Concept
Text Book Problem Generator
My current thought on a system for developing generative processes for these games is somewhat like making a framework for problems in a physics text book. With the new system I’ve setup for directly tying physics concepts to these physics games (those lists of physics topics), I think I can relate a game’s parameters (those systematic game mechanic values) to the variables of the foundational equations corresponding to that same game’s potential learning concepts. Again, using Angry Birds as an example, let’s say “Impulse and Momentum” is a potential learning concept. A basic equation for momentum is (momentum) = (mass) * (velocity). Using this information, we can see that varying any parameters equivalent to or pertaining to the variables in this equation will require the player to “solve” the new “problem” presented to them by similarly varying their responses to the system.
So for example (an example within an example), varying the bird’s mass parameter directly correlates to varying the mass in the momentum equation. If the player is still trying to meet a similar/certain momentum result, they basically have to “solve” this equation by determining the correct velocity.
I know this might seem a bit obvious, but I’m hoping it’s one of those situations where it just works out so nicely because it’s actually a good solution. This system also presents a fairly basic way of ensuring different in-game scenarios feel differently. You could keep track of the values for the “problems” presented to the player, and just check if a produced “problem” has values that are “too close” to these archived values. Back to the Angry Bird example, a game scenario presented to the player that they needed momentum in the range of (10 kg*m/s – 15 kg*m/s) with a bird of mass 5 kg (so solution range velocity is (2 m/s – 3 m/s)). The next produced scenario is a momentum range of (11 kg * m/s – 16 kg * m/s) with a bird of mass 5 kg (solution range velocity is (2.2 m/s – 3.2 m/s); maybe the system throws this out and generates a new scenario because it sees the momentum range, mass, and solution velocity are all very similar to something produced before.
The needed “distance away” from an archived problem could also be a weighted, combined distance of all the variables that could be tweaked depending on how you want to setup the system. This way, maybe you have another problem with a similar solution value (like the (2 m/s – 3m/s)), but the momentum and mass involved in the scenario are so different that it still feels like a different, interesting experience.