Skip to content
Log in
Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Gil Bub

View on Semantic Scholar

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#reinforcement learning Open access Sep 2026

Code for "Reinforcement learning discovers new mechanisms of reentry in excitable media"

Code associated with the manuscript “Reinforcement learning discovers new mechanisms of reentry in excitable media.” This archive corresponds to the current manuscript submission and includes the cellular automaton simulations, reinforcement-learning environments and training scripts, policy evaluation, simulations in the geometries studied in the manuscript, and computational figure-generation code.

Thomas Bury, Glisant Plasa, José Miguel Romero Sepúlveda et al. · 0 citations
#reinforcement learning Open access Sep 2026

Code for "Reinforcement learning discovers new mechanisms of reentry in excitable media"

Code associated with the manuscript “Reinforcement learning discovers new mechanisms of reentry in excitable media.” This archive corresponds to the current manuscript submission and includes the cellular automaton simulations, reinforcement-learning environments and training scripts, policy evaluation, simulations in the geometries studied in the manuscript, and computational figure-generation code.

Thomas Bury, Glisant Plasa, José Miguel Romero Sepúlveda et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.