gBcs
gBcs is an acronym that appears in multiple disciplines, most commonly as shorthand for a generalized Bayesian control system. In this context, gBcs denotes a theoretical framework for autonomous decision making under uncertainty that combines Bayesian inference with principles from optimal control. The aim is to produce policies that are probabilistically informed and robust to model mismatch and non-stationary environments.
A gBcs typically represents a probabilistic state-space model of the world, where the agent maintains a posterior
In practice, gBcs is primarily discussed in theoretical and experimental contexts within robotics and AI research.
Other uses of the acronym appear in different domains, including distributed computing and biology, but these