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@@ -13,7 +13,7 @@ Genetic algorithms (GAs) are optimization techniques inspired by the process of
- **Selection:** The process of choosing the best-performing solutions to carry forward.
- **Crossover and Mutation:** Methods to combine and modify solutions, creating new ones that explore the problem space.
Through repeated iterations, GAs converge toward optimal or near-optimal solutions, making them highly effective for solving complex, dynamic problems. GAs have recently gained momentum with the development of the Push 3 language by Lee Spector. Push 3’s compact and efficient architecture shares similarities with stack-based virtual machine systems like the Ethereum Virtual Machine (EVM). Although not designed specifically for EVMs, Push 3’s simplicity and flexibility make it conceptually compatible with blockchain execution environments. Push 3 has achieved milestones such as evolving programs for quantum computers and supporting autoconstructive evolution. A Push 3 VM could facilitate the deployment of genetic algorithms in decentralized systems, leveraging Push 3’s support for expressive program evolution and adaptive behavior in tasks like resource optimization.
Through repeated iterations, GAs converge toward optimal or near-optimal solutions, making them highly effective for solving complex, dynamic problems. GAs have recently gained momentum with the development of the [Push 3 language](http://faculty.hampshire.edu/lspector/push3-description.html) by Lee Spector. Push 3’s compact and efficient architecture shares similarities with stack-based virtual machine systems like the Ethereum Virtual Machine (EVM). Although not designed specifically for EVMs, Push 3’s simplicity and flexibility make it conceptually compatible with blockchain execution environments. Push 3 has achieved milestones such as evolving [programs for quantum computers](https://faculty.hampshire.edu/lspector/aqcp/) and supporting autoconstructive evolution. A Push 3 VM could facilitate the deployment of genetic algorithms in decentralized systems, leveraging Push 3’s support for expressive program evolution and adaptive behavior in tasks like resource optimization.
## On Agents