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TECS Engine
Discrete dynamic routing system for element-slot interaction
Discrete dynamic system simulation with moving elements and hash aggregation. - Jandos77/TECS_engine
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 👇
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
On the analytics side, TECS Engine competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how TECS Engine performed against the three products that launched closest to it on the same day.
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.
For a complete overview of TECS Engine including community comment highlights and product details, visit the product overview.
Jandos Mámbetáli