Journal ArticleDOI
Depth-first iterative-deepening: an optimal admissible tree search
TLDR
This heuristic depth-first iterative-deepening algorithm is the only known algorithm that is capable of finding optimal solutions to randomly generated instances of the Fifteen Puzzle within practical resource limits.About:
This article is published in Artificial Intelligence.The article was published on 1985-09-01. It has received 1698 citations till now. The article focuses on the topics: Iterative deepening depth-first search & Search algorithm.read more
Citations
More filters
Book
Metaheuristics: From Design to Implementation
TL;DR: This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling.
Book
Multiagent Systems
TL;DR: This second edition has been completely revised, capturing the tremendous developments in multiagent systems since the first edition appeared in 1999.
Journal ArticleDOI
Motion Planning in Dynamic Environments Using Velocity Obstacles
Paolo Fiorini,Zvi Shiller +1 more
TL;DR: This paper presents a method for robot motion planning in dynamic environments that consists of selecting avoidance maneuvers to avoid static and moving obstacles in the velocity space, based on the rental positions and velocities of the robot and obstacles.
Heuristic Motion Planning in Dynamic Environments Using Velocity Obstacles
P. Fiorini,Z. Shiller +1 more
TL;DR: In this paper, the authors present heuristic methods for motion planning in dynamic environments, based on the concept of Velocity Obstacle (VO), which is a heuristic method for motion prediction in a dynamic environment.
Book
Artificial Intelligence: A New Synthesis
TL;DR: Intelligent agents are employed as the central characters in this new introductory text and Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI.
References
More filters
Book
Human Problem Solving
TL;DR: The aim of the book is to advance the understanding of how humans think by putting forth a theory of human problem solving, along with a body of empirical evidence that permits assessment of the theory.
Journal ArticleDOI
A Formal Basis for the Heuristic Determination of Minimum Cost Paths
TL;DR: How heuristic information from the problem domain can be incorporated into a formal mathematical theory of graph searching is described and an optimality property of a class of search strategies is demonstrated.
Book
Principles of Artificial Intelligence
TL;DR: This classic introduction to artificial intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval.
Book
Learning to solve problems by searching for macro-operators
TL;DR: It is concluded that the macro technique is a valuable addition to the class of weak methods, that macro-operators constitute an interesting and important type of knowledge, and that searching for macros may be a useful general learning paradigm.