Game Development
You are currently browsing the archive for the Game Development category.
(Original Image by everyone’s idle.)
This post was a originally published on Luma Labs, now dead.
As old as stimulus-response techniques are, they still form an important part of many AI systems, even if it is a thin layer underneath a sophisticated decision, planning, or learning system. In this tutorial I give some advice to their design and implementation, mostly out of experience gained from implementing the AI for some racing games.
A stimulus response agent (or a reactive agent) is an agent that takes inputs from its world through sensors, and then takes action based on those inputs through actuators. Between the stimulus and response, there is a processing unit that can be arbitrarily complex. An example of such an agent is one that controls a vehicle in a racing game: the agent “looks” at the road and nearby vehicles, and then decides how much to turn and break.
Read the rest of this entry »
Tags: AI, artificial intelligence, convolution, filtering, Kalman filter, Mathematics, PID controller, racing game ai, random, random steering, response curve, Special Numbers Library, stimilus response agent, system design
Tools for editing game levels and AI for your own games are nice to have, but it is not always practical to implement these for small projects, nor is it affordable to buy them off-the-shelf or bundled with expensive middleware.
In the Dev.Mag article Guerrilla Tool Development, I give some ideas for getting some useful tools on a tight budget. Check it out!
24 October 2009 |
I wrote an article for Dev.Mag covering some techniques for working with seamless tile sets such as making blend tiles, getting more variety with procedural colour manipulation, tile placement strategies, and so on.
Check it out!
The Python Image Code has also been updated with some of the algorithms explained in the article.
28 May 2009 |
A cellular automata system is one of the best demonstrations of emergence. If you do not know what cellular automata (CA) is, then you should go download Conway’s Game of Life immediately:
Conway’s Game of Life
Essentially, CA is a collection of state machines, updated in discrete time intervals. The next state of one of these depends on the current state as well as the states of neighbours. Usually, the state machines correspond to cells in a grid, and the neighbours of a cell are the cells connected to that cell. For a more detailed explanation, see the Wikipedia article.
Even simple update rules can lead to interesting behaviour: patterns that cannot be predicted from the rules except by running them. With suitable rules, CA can simulate many systems:
- Natural phenomena: weather, fire, plant growth, migration patterns, spread of disease.
- Socio-economic phenomena: urbanisation, segregation, construction and property development, traffic, spread of news.
Read the rest of this entry »
Tags: 2D, AI, blending, cellular automata, Conway's game of life, Dev.Mag, diffusion, discrete dynamics, disease simulation, fire simulation, Game Maker, grids, optimisation, probability, random, sampling, Simulation, social dynamics, tiles
Random steering is often a useful for simulating interesting steering motion. In this post we look at components that make up a random steering toolkit. These can be combined in various ways to get agents to move in interesting ways.
You might want to have a look at Craig Reynolds’ Steering Behaviour for Autonomous Characters — the wander behaviour is what is essentially covered in this tutorial. The main difference is that we control the angle of movement directly, while Reynolds produce a steering force. This post only look at steering — we assume the forward speed is constant. All references to velocity or acceleration refers to angular velocity and angular acceleration.
Whenever I say “a random number”, I mean a uniformly distributed random floating point value between 0 and 1.
Read the rest of this entry »
Tags: 2D, AI, artificial intelligence, blending, C++, Game Development, Game Maker, Perlin noise, probability, random, random distribution, random motion, random steering, response curve, Reynolds, sampling, Simulation, steering bahaviors, steering behaviours, vector field, wander, white noise
The quadtree is an important 2D data structure and forms the core of many spatial algorithms, including compression, collision detection, and stitching algorithms. Below you can download general purpose quadtree implementations in Java and Python.
The code accompanies the Quadtrees article in Dev.Mag Issue 26. The tutorial explains how the implement a quadtree that can be use to store 2D data efficiently, lists what considerations there are in real-world applications, and gives some debugging tips.
Channels Compressed Simultaneously
 |
 |
| The original image (by smcgee). |
The image after being loaded into a quadtree. |
Read the rest of this entry »
Tags: 2D, AI, compression, computer graphics, Dev.Mag, Game Development, Image Processing, Python, quadtree, quadtrees
Google App Engine has many properties that makes it suitable for indie development. Two articles in Dev.Mag look at GAE for game development (Issue 24 and Issue 25). The first is an overview of Google App Engine, with some focus on games. The second is a tutorial that explains the implementation of “Guess a Number” on Google App Engine, for which you can download the code. For the tutorial you will need:
Read the rest of this entry »
Tags: AI, Dev.Mag, Django, editor, Game Development, Google App Engine, Python, Web Development
Game Maker is a great tool; it is especially suited for rapid development and small projects. However, as a project becomes bigger, it becomes more difficult to find things, easier to break it, and generally harder to work on. This is of course true for any production environment, and there are many things you can do to tame the beast of scale. Here are 60 things to make Game Maker projects more maintainable.
Read the rest of this entry »
Tags: AI, editor, Game Development, Game Maker, good practices, maintainability, random, Simulation, tiles
Recent Comments