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Instinct slot

As explained in Evolutionary Deep Learning: Genetic algorithms and neural networks

An instinct slot is a designated position in a neural network that can contain a reusable instinct function or layer.

An instinct slot is a designated neural-network position containing a reusable function or layer. Multiple slots form a shared instinct pool while environment-specific input and output layers remain trainable. section 12.6

A practical instinct-slot design:

  • Construct the network with Keras’s functional API, passing layer blocks through an instincts list. section 12.6

Instinctual DQN

A DQN uses three middle instinct slots whose outputs are concatenated before an environment-specific output layer, allowing one network structure to serve multiple environments. section 12.6

How Evolutionary Deep Learning: Genetic algorithms and neural networks covers it

How deep it goes
Defines slot placement, functional composition, environment-specific boundaries, and evolutionary selection through executable listings.
Examples
Demonstrates three shared middle slots, two DQN environments, concatenated branches, and evolved layer-choice genomes.
What it assumes
Assumes familiarity with DQN or deep reinforcement learning and points to DQN material for review.
What you can do after
Build it from scratch using Keras functional models and evolve reusable layer selections across environments.
How it connects
Connects neural networks, deep reinforcement learning, DQN, Keras functional API, and evolutionary optimization.
Cover of Evolutionary Deep Learning: Genetic algorithms and neural networks
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This explainer was generated by Manning's knowledge graph from the text of Evolutionary Deep Learning: Genetic algorithms and neural networks. The section links point to the parts of the book it draws on.