Decision-making under uncertainty is at the heart of any single- and multi-agent autonomous system acting with imperfect information. The cost of solving the decision-making problem is exponential in the action and observation spaces, thus rendering it unfeasible for many online systems. In this project, we investigate a novel paradigm for efficient decision-making by breaking the original problem into simplified, easier-to-solve, problems, while providing formal performance guarantees. These guarantees are crucial for online reliable autonomy and can also be exploited for adapting the simplification to the specific problem at hand. We investigate this novel general paradigm from different perspectives, please see for more details: https://anpl-technion.github.io/research/.
