By H. M. Schwartz
The e-book starts with a bankruptcy on conventional tools of supervised studying, masking recursive least squares studying, suggest sq. mistakes tools, and stochastic approximation. bankruptcy 2 covers unmarried agent reinforcement studying. issues contain studying worth features, Markov video games, and TD studying with eligibility strains. bankruptcy three discusses participant video games together with participant matrix video games with either natural and combined suggestions. quite a few algorithms and examples are provided. bankruptcy four covers studying in multi-player video games, stochastic video games, and Markov video games, concentrating on studying multi-player grid games—two participant grid video games, Q-learning, and Nash Q-learning. bankruptcy five discusses differential video games, together with multi participant differential video games, actor critique constitution, adaptive fuzzy keep watch over and fuzzy interference platforms, the evader pursuit video game, and the protecting a territory video games. bankruptcy 6 discusses new principles on studying inside robot swarms and the cutting edge suggestion of the evolution of character traits.
• Framework for figuring out quite a few equipment and methods in multi-agent desktop learning.
• Discusses tools of reinforcement studying comparable to a couple of types of multi-agent Q-learning
• Applicable to analyze professors and graduate scholars learning electric and laptop engineering, computing device technological know-how, and mechanical and aerospace engineering