In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
In this paper we present an evolutionary approach for inferring the structure and dynamics in gene circuits from observed expression kinetics. For representing the regulatory inte...
We consider the control of interacting subsystems whose dynamics and constraints are decoupled, but whose state vectors are coupled non-separably in a single cost function of a fi...
We report on an extensive series of highly controlled human subject experiments in networked trade. Our point of departure is a simple and well-studied bipartite network exchange ...
The procedure of drug approval is time-consuming, costly and risky. Accidental findings regarding multispecificity of approved drugs led to block-busters in new indication areas. ...
Joachim von Eichborn, Manuela S. Murgueitio, Mathi...