Differentiable ABMs
ABMs are discrete
0
1
Individual updates may not differentiable
but aggregate dynamics may be!
Differentiable ABMs
\theta
\nabla_\theta \mathbb E[f(\theta)]
Enables gradient-assisted calibration such as Variational Inference
Differentiable ABMs
\nabla_\theta \mathbb E[f(\theta)]
How do we obtain this gradient?
Automatic Differentiation
Challenges
- Discreteness of the ABM microstructure
- Stochasticity
- Memory requirements
- Autoregressiveness (vanishing gradients)
Ongoing research
ICAIF
ICML
AAMAS
ICLR
JOSS
arenas slides
By nickbishop
