AgentFly is an agent-based system for a large scale air traffic simulation. It is able to simulate tens of thousands airplanes in detail, e.g. to compute fuel consumption. It also models cognitive behavior of air traffic controllers to simulate their activities and workload. The AgentFly can be used to simulate complete air traffic over US to predict future air traffic

GAČR project by Jan Faigl: Adaptive Informative Path Planning in Autonomous Data Collection in Dynamic Unstructured Environments

Agent-based algorithms for road traffic autonomous support systems: Project focusses on massive autonomous traffic system simulations mainly for the purposes of development of algorithms for autonomous traffic systems and multi-agent optimization of transportation logistics. Individual research results are cross-validated to ensure their scalability, reliability, fidelity and applicability in unified realistic autonomous traffic system.

In Computation Game Theory we study and design new algorithms for finding optimal behavior in finite sequential scenarios, where agents have to deal with limited information, uncertainty, and competing opponents. Typical examples include classical card and board games, scenarios from the security domain, or auctions