A monadic framework for reinforcement learning built on top of dotty-cps-async.
import cps.rl.*- Scored Logic Monad - Monadic abstraction for weighted search with scores (
CpsScoredLogicMonad) - RL Abstractions - Core traits for environments, agents, and models (
RLEnvironment,RLAgentBehavior,RLModelControl) - Tensor Support - Type-safe tensor operations with scope management (
TensorType,TensorScope,TensorRepresentation) - Priority Queue Data Structures - Efficient heap implementations including
PairingHeap,FingerTree, and scaled variants - Cross-Platform - Supports JVM, Scala.js, and Scala Native
Add to your build.sbt:
libraryDependencies += "io.github.dotty-cps-async" %%% "rl-logic" % "<version>"- Scala 3.3.7+
- dotty-cps-async 1.3.0
- DJL (Deep Java Library) for neural network support (JVM only)
Apache 2.0