Complex Systems

Using genetic algorithms to find distributed local algorithms that generate global collective behaviors

Our team at LabV2(ASU) [collaboration with Leidos Inc.] works on modeling agent movements in real-world maps. We use knowledge graphs to model the maps in combination with symbolic rule learning and heuristic based graph traversal algorithms to model and learn agent trajectories(both anamolous and normal).

Explores evolutionary algorithms to build neural network robot controllers for building collective behaviors

We present EVOSOPS, an evolutionary framework that searches landscapes of stochastic distributed algorithms for particles that are shown to achieve emergent behviours such as Aggregation, Separation, Photo-taxing and Object Coating.
[Artificial Life Conference (ALIFE 2024)]