Ramo
Welcome to the documentation for Ramo: Rational Agents with Multiple Objectives.
Ramo is an algorithmic game theory framework offering a collection of algorithms and utilities for computing or learning (approximate) equilibria in multi-objective games. As of now, the framework supports only Multi-Objective Normal-Form Games (MONFGs), which are the multi-objective counterpart to normal-form games.
We also provide a number of handy utilities. For example, this repository comes with a number of known and pre-analysed example games and utility functions. There are also helper functions to generate random games, scalarise games, etc. In addition, there is functionality to save and plot data resulting from experiments and a bunch more, with even more on the way!
User Guide
Algorithms