New biologically plausible
learning rules
Leonard Johard
1
My background
High school
— Programmed first neural network in C++
KTH: Engineering physics
— Specialization into machine learning and
computational biology
— Molecular biology
Scuola Superiore Sant’Anna: PhD in perceptual robotis
— Robotics
— Motor learning in humans
— Machine learning
— Deep learning
2
Purpose of neurons
Hypothesis: Neurons developed for motor
learning
• Problem formulation that circumvents
all known limitations
• Biologically plausible mechanisms – no
backpropagation or non-local
information
• New actor-critic architecture –
Explanation of dopamine
3
Learning for dopaminergic neurons
4
Applications
5
Emergent neural coding – work in progress
Current ideas: Rate-based,
sparse, population,
temporal?
New hypothesis: principal
traces
– Learning model
– Full development of
information flow
(pretraining)
6
Other research interests
– Gradient ascent
strategies
– Pseudorehearsal
– Transfer learning
– Imitation
learning
– Hive learning
– Memory
7
Thank you