Introduction

GOLEM is an open-source AI framework for optimization and learning of structured graph-based models with meta-heuristic methods. It is centered around 2 ideas:

1. Potential of meta-heuristic methods in complex problem spaces.

Focus on meta-heuristics allows approaching kinds of problems where gradient-based learning methods (notably, neural networks) can’t be easily applied, like optimization problems with multiple conflicting objectives or having combinatorial character.

2. Importance of structured models in many problem domains.

Graph-based learning enables solutions in the form of structured and hybrid probabilistic models, not to mention that a wide range of domain-specific problems have a natural formulation in the form of graphs.

Together this constitutes an approach to AI that potentially leads to structured, intuitive, interpretable methods and solutions for a wide range of tasks.

To see how you can use GOLEM go to the Quick Start Guide.