Complexity Result

Complexity results in computer science investigate the computational difficulty of solving problems, focusing on determining the time and resources required by algorithms. Current research explores the complexity of diverse problems, including probabilistic and causal reasoning, explainable AI (e.g., SHAP values), and optimization within answer set programming. These analyses utilize various techniques, such as parameterized complexity and reductions to known hard problems, to establish lower bounds and identify tractable instances. Understanding these complexities is crucial for developing efficient algorithms and for guiding the design of computationally feasible models in various applications.