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Published 20 hours ago •

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Library for multi-armed bandit selection strategies, including efficient deterministic implementations of Thompson sampling and epsilon-greedy.

Reame
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Update to the oldest supported version of Go

# Problem There is a newer version of Go available. # Solution Update `go.mod` to have the oldest supported version in use

Update to the oldest supported version of Go

# Problem There is a newer version of Go available. # Solution Update `go.mod` to have the oldest supported version in use

Update to the oldest supported version of Go

# Problem There is a newer version of Go available. # Solution Update `go.mod` to have the oldest supported version in use

Update to the oldest supported version of Go

# Problem There is a newer version of Go available. # Solution Update `go.mod` to have the oldest supported version in use

Update to the oldest supported version of Go

# Problem There is a newer version of Go available. # Solution Update `go.mod` to have the oldest supported version in use

Custom errors

Add custom errors so callers can handle different error modes: - reward source unreachable - probability calculation failed - arm selection failed

Update to the oldest supported version of Go

# Problem There is a newer version of Go available. # Solution Update `go.mod` to have the oldest supported version in use

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Library for multi-armed bandit selection strategies, including efficient deterministic implementations of Thompson sampling and epsilon-greedy.