"Evolving Virtual Creatures"
K.Sims, Computer Graphics (Siggraph '94 Proceedings), July 1994, pp.15-22.
"Abstract: This paper describes a novel system for creating virtual creatures that move and behave in simulated three-dimensional physical worlds. The morphologies of creatures and the neural systems for controlling their muscle forces are both generated automatically using genetic algorithms. Different fitness evaluation functions are used to direct simulated evolutions towards specific behaviors such as swimming, walking, jumping, and following. A genetic language is presented that uses nodes and connections as its primitive elements to represent directed graphs, which are used to describe both the morphology and the neural circuitry of these creatures. This genetic language defines a hyperspace containing an indefinite number of possible creatures with behaviors, and when it is searched using optimization techniques, a variety of successful and interesting locomotion strategies emerge, some of which would be difficult to invent or build by design."

"Evolving 3D Morphology and Behavior by Competition"
K.Sims, Artificial Life IV Proceedings, ed.by Brooks & Maes, MIT Press, 1994, pp.28-39.
"Abstract: This paper describes a system for the evolution and co-evolution of virtual creatures that compete in physically simulated three-dimensional worlds. Pairs of individuals enter one-on-one contests in which they contend to gain control of a common resource. The winners receive higher relative fitness scores allowing them to survive and reproduce. Realistic dynamics simulation including gravity, collisions, and friction, restricts the actions to physically plausible behaviors.

The morphology of these creatures and the neural systems for controlling their muscle forces are both genetically determined, and the morphology and behavior can adapt to each other as they evolve simultaneously. The genotypes are structured as directed graphs of nodes and connections, and they can efficiently but flexibly describe instructions for the development of creatures’ bodies and control systems with repeating or recursive components. When simulated evolutions are performed with populations of competing creatures, interesting and diverse strategies and counter-strategies emerge."

Emergence of Collective Behavior in Evolving Populations of Flying Agents
a paper in the Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2003), published by Springer-Verlag
Abstract: We demonstrate the emergence of collective behavior in two evolutionary computation systems, one an evolutionary extension of a classic (highly constrained) flocking algorithm and the other a relatively un-constrained system in which the behavior of agents is governed by evolved computer programs. We describe the systems in detail, document the emergence of collective behavior, and argue that these systems present new opportunities for the study of group dynamics in an evolutionary context.

These proceedings serve two important functions: they address bottom-up theories of artificial intelligence and explore what can be learned from simple models such as insects about the cognitive processes and characteristic autonomy of living organisms, while also engaging researchers and philosophers in an exciting examination of the epistemological basis of this new trend.

"Artificial Evolution for Computer Graphics"
K.Sims, Computer Graphics (Siggraph '91 proceedings), July 1991, pp.319-328
This paper describes how evolutionary techniques of variation and selection can be used to create complex simulated structures, textures, and motions for use in computer graphics and animation. Interactive selection, based on visual perception of procedurally generated results, allows the user to direct simulated evolutions in preferred directions. Several examples using these methods have been implemented and are described. 3D plant structures are grown using fixed sets of genetic parameters. Images, solid textures, and animations are created using mutating symbolic lisp expressions. Genotypes consisting of symbolic expressions are presented as an attempt to surpass the limitations of fixed-length genotypes with predefined expression rules. It is proposed that artificial evolution has potential as a powerful tool for achieving flexible complexity with a minimum of user input and knowledge of details.


Using Genetic Algorithms to Generate Evolutionary Art in C# and .Net
by Michael Gold.
This article deals with using genetic algorithms to create fitness functions that produce evolutionary art on a Windows Form. Includes links to source code.

L-systems: from the theory to visual models of plants.
Przemyslaw Prusinkiewicz, Mark Hammel, Jim Hanan, and Radomir Mech.
In M. T. Michalewicz, editor, Proceedings of the 2nd CSIRO Symposium on Computational Challanges in Life Sciences. CSIRO Publishing, 1996. To appear.
"Abstract: Recent advances in computer graphics have made it possible to visualize mathematical models of biological structures and processes with unprecedented realism. The resulting images, animations, and interactive systems are useful as research and educational tools in developmental biology and ecology. Prospective applications also include computer-assisted landscape architecture, design of new varieties of plants, and crop yield prediction. In this paper we revisit foundations of the applications of L-systems to the modeling of plants, and we illustrate them using recently developed sample models."

Modeling and Visualization of Biological Structures.
Przemyslaw Prusinkiewicz.
In Proceeding of Graphics Interface '93, pages 128-137, May 1993. Held in Toronto, Ontario, 19-21 May 1993.
"Abstract: Rapid progress in the modeling of biological structures and simulation of their development has occurred over the last few years. It has been coupled with the visualization of simulation results, which has lead to a better understanding of morphogenesis and given rise to new procedural techniques for realistic image synthesis. This paper characterizes selected models of morphogenesis with a significant visual component."

The Algorithmic Beauty of Plants
by P. Prusinkiewicz and A. Lindenmayer
Book Description:
This book is the first comprehensive volume on the computer simulation of plant development. It contains a full account of the algorithms used to model plant shapes and developmental processes, Lindenmayer systems in particular. With nearly 50 color plates, the spectacular results of the modelling are vividly illustrated.

We have developed a system built around a pipeline of tools that address these tasks. The terrain is designed using an interactive graphical editor. Plant distribution is determined by hand (as one would do when designing a garden), by ecosystem simulation, or by a combination of both techniques. Given parametrized procedural models of individual plants, the geometric complexity of the scene is reduced by {\em approximate instancing}, in which similar plants, groups of plants, or plant organs are replaced by instances of representative objects before the scene is rendered. The paper includes examples of visually rich scenes synthesized using the system."

"Artificial life embodies a recent and important conceptual step in modem science: asserting that the core of intelligence and cognitive abilities is the same as the capacity for living. The recent surge of interest in artificial life has pushed a whole range of engineering traditions, such as control theory and robotics, beyond classical notions of goal and planning into biologically inspired notions of viability and adaptation, situatedness and operational closure.

These proceedings serve two important functions: they address bottom-up theories of artificial intelligence and explore what can be learned from simple models such as insects about the cognitive processes and characteristic autonomy of living organisms, while also engaging researchers and philosophers in an exciting examination of the epistemological basis of this new trend."