2026-08-12 –, Room 6
Decisions often affect the dynamics of a system. DecisionSystem is a unified way of capturing both dynamics and decisions of complex systems.
Real systems don't just evolve, they respond. DecisionSystems is a unified way of capturing physics simulation and decision-making, letting you model the full cycle: simulate dynamics, observe state, decide, act, repeat.
A vehicle braking system. A drug dosing schedule. A spacecraft attitude controller. What these share is a fundamental loop: physics evolves continuously, an agent decides discretely, and those decisions reshape the physics.
DecisionSystems.jl provides an optimized API to design experiments to define these dynamics in Dyad (ModelingToolkit) and add decision parameters to iteratively update actions based on MDP, POMDP and RL environments. The library handles: state extraction, integrator stepping, action application, and belief tracking under uncertainty.
Using examples, the talk walks through the core idea, its generalizations, and what it unlocks for hybrid physical-decision systems in Julia, covering both current features and what's planned.
He builds Dyad Agent at JuliaHub. He is leveraging generative AI and scientific AI to radically change how modeling and simulation is done.
He loves to code, paint, write and trek. He likes Julia ecosystem and contributes to it.