Penalized/Constrained Distance Function

Alex · 2012-04-11T17:43:44

Assume a character is located on a n by n grid and has to reach a certain entry on that grid. Its current position is (x1,y1). Also on the same grid is an enemy with coordinates (x2,y2). Each step algorithm randomly generates new candidate locations for the hero (if there are k candidates then there is a kx2 matrix of new potential locations. What I need is some distance objective function to compare the candidates. I'm currently using d1 - c * d2, where d1 is distance to the objective (measure in terms of number of pixels for each axis), d2 is distance to the enemy and c is some coefficient (this is very much like a set-up for Lagrangian). It's not working very well though. I'd be quite keen to learn how what constrained distance function are used for similar cases. Any suggestions or references to articles are very much appreciated.

Artificial Intelligence Programming

Started by ater1980 April 09, 2012 07:18 AM

9 comments, last by ApochPiQ 12 years ago

ApochPiQ

23,138

April 11, 2012 05:43 PM

If your obstacles are moving, you probably also want to look into steering systeems, particularly the canonical "Boids" demo by Craig Reynolds.

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Penalized/Constrained Distance Function

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