In applied mathematics, proto-value functions (PVFs) are automatically learned basis functions that are useful in approximating task-specific value functions, providing a compact representation of the powers of transition matrices. They provide a novel framework for solving the credit assignment problem. The framework introduces a novel approach to solving Markov decision processes (MDP) and reinforcement learning problems, using multiscale spectral and manifold learning methods. Proto-value functions are generated by spectral analysis of a graph, using the graph Laplacian.
Attributes | Values |
---|---|
rdfs:label |
|
rdfs:comment |
|
dcterms:subject | |
Wikipage page ID |
|
Wikipage revision ID |
|
Link from a Wikipage to another Wikipage |
|
sameAs | |
dbp:wikiPageUsesTemplate | |
has abstract |
|
prov:wasDerivedFrom | |
page length (characters) of wiki page |
|
foaf:isPrimaryTopicOf | |
is Link from a Wikipage to another Wikipage of | |
is Wikipage redirect of | |
is foaf:primaryTopic of |