Mastodawn

DeepMind's AlphaEvolve strikes again:

After recovering 0.7% of global GCP compute through better scheduling algos, AlphaEvolve helped FM Logistics achieve "10.4% improvement in routing efficiency over the previous best solution", leading to "15,000+ fewer kilometers of warehouse travel per year at full operational scale".

It's really nice to see evolutionary algorithms make a comeback. AlphaEvolve uses an LLM (Gemini) as as a mutation function, and using similar mutate-evaluate-select loops typical of traditional evolutionary algorithms.

https://cloud.google.com/blog/products/ai-machine-learning/how-fm-logistic-tackled-the-traveling-salesman-problem-at-warehouse-scale-with-alphaevolve

#AlphaEvolve #DeepMind #EvolutionaryAlgorithms

How FM Logistic tackled the traveling salesman problem at warehouse scale with AlphaEvolve | Google Cloud Blog

In a warehouse spanning eight football fields, with more than 17,700 picking locations, this Polish company was able to optimize package sorting thanks to AI tools from Google DeepMind.

Google Cloud Blog

Jenetics GA Mar 23

GIANT: General intelligent AgeNt trainer.
https://doi.org/10.1016/j.softx.2026.102607
#Jenetics #MachineLearning #EvolutionaryAlgorithms #GeneticProgramming #GeneticAlgorithm #Optimization #Games #MultiAgentSystems

W8MEJ Feb 10

What if your network wanted to be secure? 🧵 In Episode 1 of "The Morphogenetic SOC," we’re using Michael Levin’s TAME framework to redefine cyber defense. How do you control a system? Level 1: Rewire hardware. Level 2: Modify setpoints. Level 3: Reward behavior. Level 4: Persuade with reasons. Which level is your WAF? #CyberSecurity #AI #zeroknowledge #multiplepartycompute #TAME #evolutionaryalgorithms #agentic #SOC #securityengineering https://open.spotify.com/episode/4Pamgs6PUITRSHUUSFBRu7?si=-nEhwCSoSamkJPtHNe4IiQ&nd=1&dlsi=b9a7fc3ef2914a8f

The End of the Machine Metaphor in Cybersecurity

Zero Noise Collective · Episode

Spotify

Anthony Jan 5

I came across a post on LinkedIn about evolutionary computation, and opted to post this in response:
I never stopped using evolutionary computation. I'm even weirder and use coevolutionary algorithms. Unlike EC, the latter have a bad reputation as being difficult to apply, but if you know what you're doing (e.g. by reading my publications 😉) they're quite powerful in certain application areas. I've successfully applied them to designing resilient physical systems, discovering novel game-playing strategies, and driving online tutoring systems, among other areas. They can inform more conventional multi-objective optimization.

Many challenging problems are not easily "vectorized" or "numericized", but might have straightforward representations in discrete data structures. Combinatorial optimization problems can fall under this umbrella. Techniques that work directly with those representations can be orders of magnitude faster/smaller/cheaper than techniques requiring another layer of representation (natural language for LLMs, vectors of real values for neural networks). Sure, given enough time and resources clever people can work out a good numerical re-representation that allows a deep neural network to solve a problem, or prompt engineer an LLM. But why whack at your problem with a hammer when you have a precision instrument?
I started to put up notes about (my way of conceiving) coevolutionary algorithms on my web site, here. I stopped because it's a ton of work and nobody reads these as far as I can tell. Sound off if you read anything there!

#AI #GenAI #GenerativeAI #LLMs #EvolutionaryComputation #GeneticAlgorithms #GeneticProgramming #EvolutionaryAlgorithms #CoevolutionaryAlgorithms #Cooptimization #CombinatorialOptimization #optimization

coevolutionary algorithms

Anthony Bucci's personal web site

Anthony Bucci

Reddit Tech VN Bot Jan 5

LoongFlow: Khung làm việc giúp Agent "tự tiến hóa" bằng Thuật toán Tiến hóa (EA). Thay vì prompt tĩnh, LoongFlow tối ưu tự động prompt và logic như "DNA" qua các thế hệ. Kết quả: độ chính xác cao hơn ReAct truyền thống. Mã nguồn & bài báo đã công bố. 📄💻 #LoongFlow #AI #Agent #EvolutionaryAlgorithms #MachineLearning #TríTuệNhânTạo #KhoaHọcMáyTính #AIResearch

https://www.reddit.com/r/LocalLLaMA/comments/1q4atlx/r_we_built_a_framework_to_make_agents_selfevolve/

Farooq | فاروق [Master Patata]Sep 12, 2025

So finally I published me post about the idea of byte equivalent #decompilation of the #Linux #kernel using #EvolutionaryAlgorithms in the hope that we could mainline Android phones and tablets, whose companies are violating #GPL by not releasing the kernel source code.

https://far.chickenkiller.com/computing/decompiling-the-kernel-using-ea/

I really don't know if it's possible. Or if it is, how long will it take. It's research. And research means exploring the unexplored areas. You might find a little silver, or you might find few kilograms of gold. Or you might explore the areas for 2 years and in the end, find nothing.

#GPLViolation #GeneticProgramming #Research #ResearchIdea #ComputerScience #LinuxKernel #ViolatingGPL #OptimizationProblem #EvoltiionaryAlgorithm

Decompiling the GPL violated Linux kernel using Evolutionary Algorithms

TLDR: We want to decompile a binary code, into the byte equivalent C code. We look at this from an optimization viewpoint. We have a generated C code(or AST) and we want to optimize it so when we compile it, it is equivalent to the binary code, byte by byte. And I think it’s better to use a population based optimization metaheuristic to do this. Such as Genetic Programming. Requirements to understand this post The idea I’m writing about is very deep. You need to know the current problem we have about companies violating GPL and not releasing the Linux kernel source code used in their devices. Then you need to know what an Algorithm is. What a Heuristic is. And what is the difference between them. And you also need to know what an optimization problem is. And what is our goal in these problems. After that, you need to know in this very specific optimization problem, we are not looking for “good enough” solutions unlike most other optimization problems. We are rather looking for the “perfect” solution, if we can find one.

Farooq's

N_E_O Jul 29, 2025

Do you think that the widespread use of #EvolutionaryComputation, #EvolutionaryAlgorithms etc. in combination with f.e. large models might lead to the creation of #ArtificialLife / #ALife ?