Differentiable Logic Cellular Automata
(google-research.github.io)
Imagine trying to reverse-engineer the complex, often unexpected patterns and behaviors that emerge from simple rules. This challenge has inspired researchers and enthusiasts that work with cellular automata for decades. In cellular automata, we generally approach things from the bottom-up. We choose local rules, then investigate the resulting emergent patterns.
Imagine trying to reverse-engineer the complex, often unexpected patterns and behaviors that emerge from simple rules. This challenge has inspired researchers and enthusiasts that work with cellular automata for decades. In cellular automata, we generally approach things from the bottom-up. We choose local rules, then investigate the resulting emergent patterns.
computronium – differentiable learning of stateful binary circuits
(google-research.github.io)
Imagine trying to reverse-engineer the complex, often unexpected patterns and behaviors that emerge from simple rules. This challenge has inspired researchers and enthusiasts that work with cellular automata for decades. In cellular automata, we generally approach things from the bottom-up. We choose local rules, then investigate the resulting emergent patterns.
Imagine trying to reverse-engineer the complex, often unexpected patterns and behaviors that emerge from simple rules. This challenge has inspired researchers and enthusiasts that work with cellular automata for decades. In cellular automata, we generally approach things from the bottom-up. We choose local rules, then investigate the resulting emergent patterns.
Show HN: Kartoffels – Cellular Automata, Statistics, 32-bit RISC-V
(pwy.io)
Today I've released v0.7, which spans 122 commits and brings:
Today I've released v0.7, which spans 122 commits and brings:
Bitbanging 1D Reversible Automata
(richiejp.com)
I created a demo for the GFXPrim library. It implements and displays a nearest-neighbor, one-dimensional, binary cell automata. Additionally it implements a reversible automata, which is almost identical except for a small change to make it reversible. The automata is displayed over time in two dimensions, time travels from top to bottom. Although in the reversible case time could be played backwards.
I created a demo for the GFXPrim library. It implements and displays a nearest-neighbor, one-dimensional, binary cell automata. Additionally it implements a reversible automata, which is almost identical except for a small change to make it reversible. The automata is displayed over time in two dimensions, time travels from top to bottom. Although in the reversible case time could be played backwards.
Autopoietic Networks
(gbragafibra.github.io)
A type of cellular automaton with the intent of simulating autopoiesis in an emergent manner, with a simple scaling rule and with each unit having binary state attribution and a corresponding gate associated to it.
A type of cellular automaton with the intent of simulating autopoiesis in an emergent manner, with a simple scaling rule and with each unit having binary state attribution and a corresponding gate associated to it.
Solving mazes with neural cellular automata (2021)
(umu1729.github.io)
Interactive demonstration of Neural Cellular Maze Solver. This cellular automaton is trained to output the shortest path between the two endpoints. You can interactively edit the maze input by clicking or tapping with selected maze cell types (Wall, Road, Endpoint). The state of each cell is stochastically updated depending on the state of each cell and the four-surrounding cells.
Interactive demonstration of Neural Cellular Maze Solver. This cellular automaton is trained to output the shortest path between the two endpoints. You can interactively edit the maze input by clicking or tapping with selected maze cell types (Wall, Road, Endpoint). The state of each cell is stochastically updated depending on the state of each cell and the four-surrounding cells.
Nestedly Recursive Functions
(stephenwolfram.com)
Integers. Addition. Subtraction. Maybe multiplication. Surely that’s not enough to be able to generate any serious complexity. In the early 1980s I had made the very surprising discovery that very simple programs based on cellular automata could generate great complexity. But how widespread was this phenomenon?
Integers. Addition. Subtraction. Maybe multiplication. Surely that’s not enough to be able to generate any serious complexity. In the early 1980s I had made the very surprising discovery that very simple programs based on cellular automata could generate great complexity. But how widespread was this phenomenon?