Bundles

What happens when intelligent machines must compete, cooperate, negotiate, and learn in the same environment?The answer lies at the intersection of Game Theory and Artificial Intelligence.This complete two-volume series explores how modern AI systems make strategic decisions in environments filled with uncertainty, competition, cooperation, and dynamic interactions.Inside the bundle, you'll discover:✓ Classical Game Theory and Nash Equilibrium✓ Multi-Agent Systems and Distributed Intelligence✓ Reinforcement Learning and Multi-Agent RL✓ Deep Reinforcement Learning Algorithms✓ Nash Q-Learning, Minimax-Q, and Correlated-Q✓ DQN, Actor-Critic, MADDPG, QMIX, and CTDE✓ Mechanism Design and Incentive Engineering✓ Decision Making Under Uncertainty✓ Social Choice Theory and Collective Intelligence✓ Applications in Robotics, Economics, Networks, and Cybersecurity✓ Evolutionary and Quantum Game Theory✓ AI Safety, Governance, and Alignment✓ Future Research Directions in Strategic AIFrom autonomous vehicles and intelligent robots to cybersecurity defense systems and large-scale AI simulations, this bundle provides the mathematical foundations, algorithmic techniques, and practical insights needed to understand the future of intelligent autonomous systems.Whether you are a student, researcher, engineer, educator, or AI professional, this series offers a comprehensive roadmap to mastering strategic artificial intelligence and multi-agent intelligence.