JaxLife: An Open-Ended Agentic Simulator

TL;DR

JaxLife is an open-ended artificial life simulator where neural network-based agents evolve complex behaviors like communication and tool use, aiming to understand the emergence of intelligence and culture.

Contribution

It introduces JaxLife, a novel environment capable of supporting open-ended evolution and complex emergent behaviors in neural network agents.

Findings

Agents develop rudimentary communication protocols

Emergent behaviors include agriculture and tool use

Complexity scales with computational resources

Abstract

Human intelligence emerged through the process of natural selection and evolution on Earth. We investigate what it would take to re-create this process in silico. While past work has often focused on low-level processes (such as simulating physics or chemistry), we instead take a more targeted approach, aiming to evolve agents that can accumulate open-ended culture and technologies across generations. Towards this, we present JaxLife: an artificial life simulator in which embodied agents, parameterized by deep neural networks, must learn to survive in an expressive world containing programmable systems. First, we describe the environment and show that it can facilitate meaningful Turing-complete computation. We then analyze the evolved emergent agents' behavior, such as rudimentary communication protocols, agriculture, and tool use. Finally, we investigate how complexity scales with the amount of compute used. We believe JaxLife takes a step towards studying evolved behavior in more open-ended simulations. Our code is available at https://github.com/luchris429/JaxLife