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TECS Engine

Discrete dynamic routing system for element-slot interaction

Open Source
Developer Tools
Artificial Intelligence
GitHub
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Hunted byJandos MámbetáliJandos Mámbetáli

Discrete dynamic system simulation with moving elements and hash aggregation. - Jandos77/TECS_engine

Top comment

I built TECS to explore a simple question: What if data routing was dynamic, cyclic, and resource-constrained instead of static? Most modern systems (including attention mechanisms) assume soft, continuous routing. TECS takes a different approach — elements physically “move” across slots over time, creating a discrete dynamic system: [math]p_e(t+1) = (p_e(t) + v_e) \bmod N[/math] and aggregation happens locally: [math]Y_s(t) = F_s({\varphi_e(t) \mid p_e(t)=s})[/math] This leads to interesting properties: natural resource competition emergent patterns and periodicity hybrid behavior between simulation and learning systems Originally, this started as a theoretical model of discrete dynamics, but it evolved into a working engine combining: simulation (agent-like movement) neural routing (Gumbel-Softmax) and system-level constraints I’m especially interested in feedback on: potential applications (AI / distributed systems / simulations) theoretical connections (dynamics, computation) and ideas for extending it further Happy to answer any questions 👇

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About TECS Engine on Product Hunt

Discrete dynamic routing system for element-slot interaction

TECS Engine was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #92 on the daily leaderboard. Discrete dynamic system simulation with moving elements and hash aggregation. - Jandos77/TECS_engine

TECS Engine was featured in Open Source (68.3k followers), Developer Tools (511.1k followers), Artificial Intelligence (466.4k followers) and GitHub (41.2k followers) on Product Hunt. Together, these topics include over 183.6k products, making this a competitive space to launch in.

Who hunted TECS Engine?

TECS Engine was hunted by Jandos Mámbetáli. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

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