pymdp 0.0.3
Updates include:
- more demo colab notebooks now linked on main page
- model checks in when constructing an
Agent()
(e.g. normalization checks) D
vector learning / bayesian model reduction- can pass in
E
vector (prior over policies) toAgent()
constructor - time-varying prior preferences (i.e.
C
can now be a matrix rather than having to be a vector) - updated dependencies in
setup.py
to allow forwards compatibility with newer versions of various packages