INTRODUCTION

How Does Karl Sims' Virtual Creatures Evolve?

Sims, technically, designed his virtual system by allowing the creatures to perform different behaviors such as swimming, walking, jumping, or competing for virtual resources. 

Different goals were designed for different experiments for various virtual creatures, such as swimming as the fastest in a simulated water environment. Winners completing their tasks most successfully were selected for survival. Then, their virtual genes were selected for the next generation with random gene mutation during reproduction. This process was successive, and creatures that could produce more successful performance appeared.

It should be noted that Sims did not set direct interaction with the virtual creatures. He only specified the "natural environment", which was the task goals, for the creatures, rather than manually adjusting their evolution. 

The indirect interaction design conforms with the evolutionary simulation and reflects the Red Queen's hypothesis in biology.

Karl Sims' Virtual Creatures In History

Discussion

Before Sims, animation and 3D modeling were almost entirely top-down processes; an artist had to explicitly design and keyframe every movement. Sims showed that it is possible to achieve complex, life-like motion through a bottom-up, goal-oriented process. This is the conceptual ancestor of modern procedural animation found in video games and films, where characters react dynamically to their environment instead of playing pre-baked animations.

While not the first Artificial Life project, it became the most famous and accessible example. It vividly showed that simple rules (physics, genetics, selection) could lead to emergent complexity—sophisticated behaviors and forms that were never explicitly programmed. It made abstract concepts from evolutionary biology tangible. Such Process also resonates with one concept introduced during the course: abstract human language may be interpreted in various ways. Just as the simple genetic "language" in Sims' work was interpreted by the physics engine to produce a vast diversity of unexpected creatures, the abstract instructions of human language can be interpreted by a computer in countless ways, leading to equally surprising and creative results.

Rather than meticulously programming the exact movements and evolutionary trajectories, I'm inspired to simply design the environment and the rules of interaction. The goal is to create a system where surprising and effective solutions can emerge organically, without being explicitly designed.

Conclusion