May 1, 2024
3 minute read
Adversarial Search is a branch of artificial intelligence concerned with designing algorithms and decision-making strategies in situations where multiple agents are in conflict with each other. It's a core component of many popular games, such as chess, checkers, and Go, and has applications in a wide range of fields, including computer security, economics, and military strategy.
What is Adversarial Search?
In adversarial search, two or more agents take turns making decisions to achieve their respective goals. The goal of one agent is typically to maximize its payoff, while the goal of the other agent is to minimize the payoff of the first agent. Adversarial search algorithms are designed to find the best possible decision for each agent, taking into account the possible responses of the other agents.
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Find a path to becoming a Adversarial Search. Learn more at:
OpenCourser.com/topic/n6t2e7/adversarial
Reading list
We've selected five books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Adversarial Search.
Provides a comprehensive treatment of adversarial search, written by one of the leading researchers in the field.
This classic textbook covers a wide range of AI topics, including adversarial search, and is written by two of the leading researchers in the field.
This textbook provides an introduction to multiagent systems, which are a key area of application for adversarial search.
Provides an introduction to game theory, which key foundation for adversarial search.
Provides an introduction to game theory, which key foundation for adversarial search.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/n6t2e7/adversarial
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