Jawad Ali discusses heuristic algorithms and search methods. A heuristic algorithm sacrifices optimality, accuracy, or completeness for speed in solving problems like NP-complete decision problems. Heuristic search iteratively improves solutions based on a heuristic function or cost measure, finding a good solution quickly without guaranteeing an optimal one. Examples given are swarm intelligence inspired by swarm movements in nature, tabu search preventing repetitive movements, and artificial neural networks inspired by the brain for pattern recognition. Heuristic algorithms have low time complexity and are applied to complex problems.