A Theory of Heuristic Information in Game-Tree Search


Book Description

Searching is an important process in most AI systems, especially in those AI production systems consisting of a global database, a set of production rules, and a control system. Because of the intractability of uninformed search procedures, the use of heuristic information is necessary in most searching processes of AI systems. This important concept of heuristic informatioD is the central topic of this book. We first use the 8-puzzle and the game tic-tac-toe (noughts and crosses) as examples to help our discussion. The 8-puzzle consists of eight numbered movable tiles set in a 3 x 3 frame. One cell of the frame is empty so that it is possible to move an adjacent numbered tile into the empty cell. Given two tile configurations, initial and goal, an 8-puzzle problem consists of changing the initial configuration into the goal configuration, as illustrated in Fig. 1.1. A solution to this problem is a sequence of moves leading from the initial configuration to the goal configuration, and an optimal solution is a solution having the smallest number of moves. Not all problems have solutions; for example, in Fig. 1.1, Problem 1 has many solutions while Problem 2 has no solution at all.




Heuristic Search


Book Description

Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constraint satisfaction and machine learning. While no previous familiarity with heuristic search is necessary the reader should have a basic knowledge of algorithms, data structures, and calculus. Real-world case studies and chapter ending exercises help to create a full and realized picture of how search fits into the world of artificial intelligence and the one around us. - Provides real-world success stories and case studies for heuristic search algorithms - Includes many AI developments not yet covered in textbooks such as pattern databases, symbolic search, and parallel processing units




Heuristics


Book Description

Problem-solving strartegies and the nature of Heuristic informatio n.Heuristics and problem representations. Basic Heuristic-Search procedures. Formal properties of Heuristic methods. Heuristics viewed as information provided by simplified models. Performance analysis of Heuristic methods. Abstract models for quantitative performace analysis. Complexity versus precision of admissible Heuristics. Searching with nonadmissible Heuristics. Game-playing programs. Strategies and models for game-playing programs. Performace analysis for game-searching strategies. Decision quality in game searching. Bibliography. Index.




Theory of Randomized Search Heuristics


Book Description

This volume covers both classical results and the most recent theoretical developments in the field of randomized search heuristics such as runtime analysis, drift analysis and convergence.




Search in Artificial Intelligence


Book Description

Search is an important component of problem solving in artificial intelligence (AI) and, more generally, in computer science, engineering and operations research. Combinatorial optimization, decision analysis, game playing, learning, planning, pattern recognition, robotics and theorem proving are some of the areas in which search algbrithms playa key role. Less than a decade ago the conventional wisdom in artificial intelligence was that the best search algorithms had already been invented and the likelihood of finding new results in this area was very small. Since then many new insights and results have been obtained. For example, new algorithms for state space, AND/OR graph, and game tree search were discovered. Articles on new theoretical developments and experimental results on backtracking, heuristic search and constraint propaga tion were published. The relationships among various search and combinatorial algorithms in AI, Operations Research, and other fields were clarified. This volume brings together some of this recent work in a manner designed to be accessible to students and professionals interested in these new insights and developments.




An Introduction to Default Logic


Book Description

This book is written for those who are interested in a fonnalization of human reasoning, especially in order to build "intelligent" computer systems. Thus, it is mainly designed for the Artificial Intelligence community, both students and researchers, although it can be useful for people working in related fields like cognitive psychology. The major theme is not Artificial Intelligence applications, although these are discussed throughout in sketch fonn. Rather, the book places a heavy emphasis on the fonnal development of default logic, results and problems. Default logic provides a fonnalism for an important part of human reasoning. Default logic is specifically concerned with common sense reasoning, which has recently been recognized in the Artificial Intelligence literature to be of fundamental importance for knowledge representation. Previously, fonnalized reasoning systems failed in real world environments, though succeeding with an acceptable ratio in well-defined environments. This situation enabled empirical explorations and the design of systems without theoretical justification. In particular, they could not be compared since there was no basis to judge their respective merits. Default logic turned out to be very fruitful by proving the correctness of some of them. We hope that this book will initiate other successful developments in default logic.




Intelligent Autonomous Systems, IAS--3


Book Description

A collection of papers dealing with complete systems of intelligent robots, focusing on autonomy. The contributions cover intelligent perception, intelligent planning and control, and integrated systems.




Prolog by Example


Book Description

Prolog has a declarative style. A predicate definition includes both the input and output parameters, and it allows a programmer to define a desired result without being concerned about the detailed instructions of how it is to be computed. Such a declarative language offers a solution to the software crisis, because it is shorter and more concise, more powerful and understandable than present-day languages. Logic highlights novel aspects of programming, namely using the same program to compute a relation and its inverse, and supporting deductive retrieval of informa tion. This is a book about using Prolog. Its real point is the examples introduced from Chapter 3 onwards, and so a Prolog programmer does not need to read Chapters 1 and 2, which are oriented more to teachers and to students, respec tively. The book is recommended for introductory and advanced university courses, where students may need to remember the basics about logic program ming and Prolog, before starting doing. Chapters 1 and 2 were also kept for the sake of unity of the whole material. In Chapter 1 a teaching strategy is explained based on the key concepts of Pro log which are novel aspects of programming. Prolog is enhanced as a computer programming language used for solving problems that involve objects and the relationships between objects. This chapter provides a pedagogical tour of pre scriptions for the organization of Prolog programs, by pointing out the main draw backs novices may encounter.




Logic Grammars


Book Description

Logic grammars have found wide application both in natural language processing and in formal applications such as compiler writing. This book introduces the main concepts involving natural and formal language processing in logic programming, and discusses typical problems which the reader may encounter, proposing various methods for solving them. The basic material is presented in depth; advanced material, involving new logic grammar formalisms and applications, is presented with a view towards breadth. Major sections of the book include: grammars for formal language and linguistic research, writing a simple logic grammar, different types of logic grammars, applications, and logic grammars and concurrency. This book is intended for those interested in logic programming, artificial intelligence, computational linguistics, Fifth Generation computing, formal languages and compiling techniques. It may be read profitably by upper-level undergraduates, post-graduate students, and active researchers on the above-named areas. Some familiarity with Prolog and logic programming would be helpful; the authors, however, briefly describe Prolog and its relation to logic grammars. After reading Logic Grammars, the reader will be able to cope with the ever-increasing literature of this new and exciting field.




Intelligent Planning


Book Description

"The central fact is that we are planning agents." (M. Bratman, Intentions, Plans, and Practical Reasoning, 1987, p. 2) Recent arguments to the contrary notwithstanding, it seems to be the case that people-the best exemplars of general intelligence that we have to date do a lot of planning. It is therefore not surprising that modeling the planning process has always been a central part of the Artificial Intelligence enterprise. Reasonable behavior in complex environments requires the ability to consider what actions one should take, in order to achieve (some of) what one wants and that, in a nutshell, is what AI planning systems attempt to do. Indeed, the basic description of a plan generation algorithm has remained constant for nearly three decades: given a desciption of an initial state I, a goal state G, and a set of action types, find a sequence S of instantiated actions such that when S is executed instate I, G is guaranteed as a result. Working out the details of this class of algorithms, and making the elabora tions necessary for them to be effective in real environments, have proven to be bigger tasks than one might have imagined.




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