Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.
Explores Markov chains and their applications in algorithms, focusing on user impatience and faithful sample generation.
Explores Markov chains, their properties, and algorithmic applications, emphasizing information quantification and state monotonicity.
Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.
