Selective Depth-First Search Methods

نویسندگان

  • Yngvi Björnsson
  • Tony Marsland
چکیده

In this paper we take a general look at forward pruning in tree search. By identifying what we think are desirable characteristics of pruning heuristics, and what attributes are important for them to consider, we hope to understand better the shortcomings of existing techniques, and to provide some additional insight into how they can be improved. We view this work as a first step towards the goal of improving existing forward-pruning methods.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Performance Studies of PV: an On-the-fly Model-checker for LTL-X Featuring Selective Caching and Partial Order Reduction

We present an enumerative model-checker PV that uses a new partial order reduction algorithm called Twophase. This algorithm does not use the in-stack check to implement the proviso, making the combination of Twophase with on-the-fly LTL-X model-checking based on nested depth-first search, as well as with selective state caching very straightforward. We present a thorough evaluation of PV in te...

متن کامل

Search

AI efforts to solve problems with computers which humans routinely handle by employing innate cognitive abilities, pattern recognition, perception and experience, invariably must turn to considerations of search. This Chapter explores search methods in AI, including both blind exhaustive methods and informed heuristic and optimal methods, along with some more recent findings. The search methods...

متن کامل

Heuristic Planning with SAT: Beyond Uninformed Depth-First Search

Planning-specific heuristics for SAT have recently been shown to produce planners that match best earlier ones that use other search methods, including the until now dominant heuristic state-space search. The heuristics are simple and natural, and enforce pure depth-first search with backward chaining in the standard conflictdirected clause learning (CDCL) framework. In this work we consider al...

متن کامل

Anytime Best+Depth-First Search for Bounding Marginal MAP

We introduce new anytime search algorithms that combine best-first with depth-first search into hybrid schemes for Marginal MAP inference in graphical models. The main goal is to facilitate the generation of upper bounds (via the bestfirst part) alongside the lower bounds of solutions (via the depth-first part) in an anytime fashion. We compare against two of the best current state-of-the-art s...

متن کامل

A Fast ACELP Codebook Search Method Based on Pulse Replacement and Tree Pruning

The algebraic code excited linear prediction (ACELP) algorithm has been adopted by many speech coding standards, due to low complexity and high quality in its analysis-by-synthesis optimization. One of the optimum ACELP codebook search methods is depth first tree search. Two methods based on pulse replacement and pruning of tree are already proposed for improvement the depth first tree search m...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1997