Improving Prolog Programs: Refactoring for Prolog

Logic Programming - Lecture Notes in Computer Science ◽

10.1007/978-3-540-27775-0_5 ◽

2004 ◽

pp. 58-72 ◽

Cited By ~ 2

Author(s):

Tom Schrijvers ◽

Alexander Serebrenik

Keyword(s):

Prolog Programs

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Compiling Recursive Functional Prolog Programs with List Structure into Procedural Languages

Automated Reasoning Series - Automated Reasoning ◽

10.1007/978-94-011-3488-0_10 ◽

1991 ◽

pp. 211-229 ◽

Cited By ~ 1

Author(s):

Young K. Nam ◽

Lawrence J. Henschen

Keyword(s):

List Structure ◽

Prolog Programs

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The performance of parallel Prolog programs

IEEE Transactions on Computers ◽

10.1109/12.61072 ◽

1990 ◽

Vol 39 (12) ◽

pp. 1435-1445 ◽

Cited By ~ 8

Author(s):

B.S. Fagin ◽

A.M. Despain

Keyword(s):

Prolog Programs

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On the detection of some periodic loops during the execution of Prolog programs

Banach Center Publications ◽

10.4064/-28-1-151-166 ◽

1993 ◽

Vol 28 (1) ◽

pp. 151-166

Author(s):

Dimiter Skordev

Keyword(s):

Prolog Programs

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Using Tabled Logic Programming to Solve the Petrobras Planning Problem

Theory and Practice of Logic Programming ◽

10.1017/s1471068414000295 ◽

2014 ◽

Vol 14 (4-5) ◽

pp. 697-710 ◽

Cited By ~ 4

Author(s):

ROMAN BARTÁK ◽

NENG-FA ZHOU

Keyword(s):

Monte Carlo ◽

Logic Programming ◽

Pattern Matching ◽

Planning Problem ◽

Tree Search ◽

Limited Capacity ◽

Plan Quality ◽

Monte Carlo Tree Search ◽

Improve Efficiency ◽

Prolog Programs

AbstractTabling has been used for some time to improve efficiency of Prolog programs by memorizing answered queries. The same idea can be naturally used to memorize visited states during search for planning. In this paper we present a planner developed in the Picat language to solve the Petrobras planning problem. Picat is a novel Prolog-like language that provides pattern matching, deterministic and non-deterministic rules, and tabling as its core modelling and solving features. We demonstrate these capabilities using the Petrobras problem, where the goal is to plan transport of cargo items from ports to platforms using vessels with limited capacity. Monte Carlo Tree Search has been so far the best technique to tackle this problem and we will show that by using tabling we can achieve much better runtime efficiency and better plan quality.

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