Search Results for "tiny-core-plus"

This Ruby program takes in a topology specification for an artificial neural network and emits optimized C code (using SSE intrinsics) that implements fast forward and backward propagation for that specific topology.

...Each entry follows a consistent template: motivation, strategy, pseudocode, parameter choices, variations, and references, making it easy to compare approaches. The catalog spans evolutionary algorithms, swarm intelligence, immune systems, simulated annealing, tabu search, and other metaheuristics, plus guidance on when and how to tune them. Example implementations and worked problems show how to encode solutions, define fitness, and balance exploration with exploitation. The emphasis is on pragmatism—enough theory to understand why an algorithm works, and enough detail to get it running in your environment. It’s a useful starting point for students and practitioners who want to prototype, benchmark, or hybridize algorithms without digging through scattered academic papers.