The "Algorithms for Intelligent Systems" book series primarily focuses on the analysis, development, and application of algorithms for intelligent systems. It covers a wide range of topics including autonomous agents, multi-agent systems, behavioral modeling, reinforcement learning, game theory, machine learning, meta-heuristic search, optimization, planning and scheduling, artificial neural networks, evolutionary computation, swarm intelligence, and more. This series contributes to the advancement of intelligent systems research by providing a comprehensive platform for sharing recent advancements, modifications, and applications in the field. It benefits graduate students, post-graduate students, and researchers by offering a broader perspective on the latest trends and challenges in intelligent systems, fostering interdisciplinary collaboration, and promoting practical problem-solving approaches.