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Advice For Aspiring Indie Game Developers
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Rendering and Simulation in an Off-Road Driving Game
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Hide Objects Blocking Player View
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GDC 2013: Interview with Jakob Schmid
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Ten Things to Achieve When Starting 3D Programming
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Useless Snippet #1: Transform Vec3f by Matrix4x4f
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Improving a Sprite-Based Rendering Procedure
Smarter Steering: Using Context for Direction
Published in Artificial Intelligence
By Mike Lewis - Combine the power of steering and flocking models with contextual information to build a simple but powerful local navigation system.
Fast Heuristic Search for RTS Game Combat Scenarios
Published in Artificial Intelligence
By David Churchill and Abdallah Saffidine and Michael Buro - research paper from the 2012 Artificial Intelligence and Interactive Digital Entertainment conference
Incorporating Search Algorithms into RTS Game Agents
Published in Artificial Intelligence
By David Churchill and Michael Buro - research paper from the 2012 Artificial Intelligence and Interactive Digital Entertainment conference RTS Workshop
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Smarter Steering: Using Context for Direction UNDER REVIEW
Jun 03 2013 11:08 AM | Posted By Mike Lewis
in Artificial Intelligence
Combine the power of steering and flocking models with contextual information to build a simple but powerful local navigation system.
Tagged With: ai steering context steering movement
Fast Heuristic Search for RTS Game Combat Scenarios UNDER REVIEW
Oct 16 2012 06:35 AM | Posted By David Churchill and Abdallah Saffidine and Michael Buro
in Artificial Intelligence
research paper from the 2012 Artificial Intelligence and Interactive Digital Entertainment conference
Tagged With: rts heuristic ai research
Incorporating Search Algorithms into RTS Game Agents UNDER REVIEW
Oct 15 2012 08:14 AM | Posted By David Churchill and Michael Buro
in Artificial Intelligence
research paper from the 2012 Artificial Intelligence and Interactive Digital Entertainment conference RTS Workshop
Tagged With: rts agents ai
A new method to speed up path finding
Jan 03 2012 08:18 AM | Posted By Niu Jian
in Artificial Intelligence
The method is simple.
Red grid is block grid,Green grid can walk.
first,Pre process on map to get datas that we need:
1) The map is divided into many regions, each region consist of a number of grids, these regions must be convex polygon(int most cases,they are rectangulars), there are not block grids in these regions.
2) then generate the shortest path information between regions, such...
Tagged With: grid region path regions shortest information dest source grids
Build-Order Optimization in StarCraft UNDER REVIEW
Oct 14 2011 08:04 PM | Posted By David Churchill and Michael Buro
in Artificial Intelligence
Academic research paper from the 2011 Artificial Intelligence and Interactive Digital Entertainment conference
Tagged With: research rts
Navigation Graph Generation
Jun 28 2011 03:20 PM | Posted By Igor Borovikov
in Artificial Intelligence
OverviewNavigation graph remains a useful alternative to navigation mesh and may offer certain advantages depending on a game's environment. This article discusses several approaches to navigation graph generation: from an automated one based on Delaunay triangulation to a completely automatic method derived from triangulation of navigable areas and dual graph of triangulation.The article u...
The Core Mechanics of Influence Mapping
Jun 07 2011 10:00 PM | Posted By Alex J. Champandard
in Artificial Intelligence
.Influence maps have been around since the very early days of game AI, tracing their history back to real-time strategy games over a decade ago. Since then, influence maps have become a cornerstone technique for game developers, and are even starting to become prevalent in first-person shooters as well (e.g. KILLZONE 2/3). In this tutorial, you'll learn about some of the motivation fo...
Vehicle Control with Neural Networks
Sep 01 2003 05:34 AM | Posted By Philippe Kunzle
in Artificial Intelligence
AbstractUsing a neural network for the brain, we want a vehicle to drive by itself avoiding obstacles. We accomplish this by choosing the appropriate inputs/outputs and by carefully training the neural net. We feed the network with distances of the closest obstacles around the vehicle to imitate what a human driver would see. The output is the acceleration and steering of the vehicle. We also n...