Tags / RL

• MCTS in Swift AlphaZero and MCTS implementation for OpenSpiel This project is a work-in-progress fork of the OpenSpiel library. It adds an MCTS implementation that will form the basis of a simple AlphaZero trainer. The design leverages some of the powerful type system abilities of Swift to achieve a maximally composable design, which allows the underlying tree-building implementation to be shared between several algorithms (various variants of MCTS, as well as Alpha-Beta search), which additionally makes them very clear. The fundamental Swift constructs …

• Spieeltjie experiment with multi-agent RL on zero-sum differentiable games Spieeltjie is a single-file package for doing simple experiments with multi-agent reinforcement learning on symmetric zero-sum games. For more information see “Open-ended learning in Symmetric Zero-Sum Games” and “A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning”. The name “spieeltjie” comes from the Afrikaans word for “tournament”. […] This first set of images shows trajectories when starting from a set of random …