Creating an HGF and HGF agent
In this section we will cover the types of nodes, their parameters and the rules for structuring your own HGF.
Overview
Building principles
The following rules apply for connecting nodes, when customizing your own HGF structure:
Parameters
- no parameters in the categorical state node
The states of Categorical input nodes and parameters
- input value
Parameters
- no parameters in the categorical state node
Continuous Nodes
The states of Continuous state nodes and parameters
States
- posterior mean
- posterior precision
- value prediction error
- volatility prediction error
- prediction mean
- prediciton volatility
- prediction precision
- auxiliary prediction precision
Parameters
- evolution rate (default is 0)
- value coupling
- volatility coupling
- initial mean (default is 0)
- initital precision (default is 0)
The states of Continuous input nodes and parameters
- input value
- value prediction error
- volatility prediction error
- prediction volatility
- prediction precision
Parameters
- input noise (default is 0)
- value coupling
- volatility coupling
Binary state node rules:
- Can only have exactly one value parent
- Can only have excatly one value child
- Can only have a contionus state node as value parent
continuous state node rules:
- Can’t have binary input node as child
- Can’t have binary input node as volatility child
- Contionus state node having a binary input node as volatility child
- Can’t have contionus input node as value child while also having volatility children
- Can’t have the same value parent as volatility parent
- Can’t have the same value child as volatility child
Categorical state node rules:
- Can only have exactly one value child
- Can only have categorical input node as child
- Can only have binary state node as parents
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