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Thomas Miconi

4 accepted papers

2023

Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning

ICML 2023poster

A hallmark of intelligence is the ability to autonomously learn new flexible, cognitive behaviors - that is, behaviors where the appropriate action depends not just on immediate stimuli (as in simple reflexive stimulus-response associations), but on contextual information that must be adequately acq…

2020

Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients

ICML 2020poster

In this paper, we introduce a novel form of value function, $Q(s, s’)$, that expresses the utility of transitioning from a state $s$ to a neighboring state $s’$ and then acting optimally thereafter. In order to derive an optimal policy, we develop a forward dynamics model that learns to make next-st…

Cited by 26SourcePDFScholar
2019

Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity

ICLR 2019poster

The impressive lifelong learning in animal brains is primarily enabled by plastic changes in synaptic connectivity. Importantly, these changes are not passive, but are actively controlled by neuromodulation, which is itself under the control of the brain. The resulting self-modifying abilities of th…

Cited by 105SourcePDFScholar
2018

Differentiable plasticity: training plastic neural networks with backpropagation

ICML 2018oral

How can we build agents that keep learning from experience, quickly and efficiently, after their initial training? Here we take inspiration from the main mechanism of learning in biological brains: synaptic plasticity, carefully tuned by evolution to produce efficient lifelong learning. We show that…