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Computer Go: an AI Oriented Survey
 Artificial Intelligence
, 2001
"... Since the beginning of AI, mind games have been studied as relevant application fields. Nowadays, some programs are better than human players in most classical games. Their results highlight the efficiency of AI methods that are now quite standard. Such methods are very useful to Go programs, bu ..."
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Cited by 98 (20 self)
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Since the beginning of AI, mind games have been studied as relevant application fields. Nowadays, some programs are better than human players in most classical games. Their results highlight the efficiency of AI methods that are now quite standard. Such methods are very useful to Go programs, but they do not enable a strong Go program to be built. The problems related to Computer Go require new AI problem solving methods. Given the great number of problems and the diversity of possible solutions, Computer Go is an attractive research domain for AI. Prospective methods of programming the game of Go will probably be of interest in other domains as well. The goal of this paper is to present Computer Go by showing the links between existing studies on Computer Go and different AI related domains: evaluation function, heuristic search, machine learning, automatic knowledge generation, mathematical morphology and cognitive science. In addition, this paper describes both the practical aspects of Go programming, such as program optimization, and various theoretical aspects such as combinatorial game theory, mathematical morphology, and MonteCarlo methods. B. Bouzy T. Cazenave page 2 08/06/01 1.
Rules and Strategies for Transforming Functional and Logic Programs
 ACM Computing Surveys
, 1996
"... We present an overview of the program transformation methodology, focusing our attention on the socalled `rules + strategies' approach in the case of functional and logic programs. The paper is intended to offer an introduction to the subject. The various techniques we present are illustrated ..."
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Cited by 83 (5 self)
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We present an overview of the program transformation methodology, focusing our attention on the socalled `rules + strategies' approach in the case of functional and logic programs. The paper is intended to offer an introduction to the subject. The various techniques we present are illustrated via simple examples. A preliminary version of this report has been published in: Moller, B., Partsch, H., and Schuman, S. (eds.): Formal Program Development. Lecture Notes in Computer Science 755, Springer Verlag (1993) 263304. Also published in: ACM Computing Surveys, Vol 28, No. 2, June 1996. 3 1 Introduction The program transformation approach to the development of programs has first been advocated by [BurstallDarlington 77], although the basic ideas were already presented in previous papers by the same authors [Darlington 72, BurstallDarlington 75]. In that approach the task of writing a correct and efficient program is realized in two phases: the first phase consists in writing an in...
What Not to Do When Writing an Interpreter for Specialisation
 In Danvy et al
, 1996
"... . A partial evaluator, given a program and a known "static" part of its input data, outputs a specialised or residual program in which computations depending only on the static data have been performed in advance. Ideally the partial evaluator would be a "black box" able to extr ..."
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Cited by 32 (3 self)
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. A partial evaluator, given a program and a known "static" part of its input data, outputs a specialised or residual program in which computations depending only on the static data have been performed in advance. Ideally the partial evaluator would be a "black box" able to extract nontrivial static computations whenever possible; which never fails to terminate; and which always produces residual programs of reasonable size and maximal efficiency, so all possible static computations have been done. Practically speaking, partial evaluators often fall short of this goal; they sometimes loop, sometimes pessimise, and can explode code size. A partial evaluator is analogous to a spirited horse: while impressive results can be obtained when used well, the user must know what he/she is doing. Our thesis is that this knowledge can be communicated to new users of these tools. This paper presents a series of examples, concentrating on a quite broad and on the whole quite successful application ...
Verifying CTL Properties of Infinite State Systems by Specializing Constraint Logic Programs
, 2001
"... this paper we assume that a system makes transitions from states to states and its evolution can be formalized using a computation tree which is dened as follows. Given a system S and its initial state s 0 , the root of the computation tree for S is s 0 , and every node s i of the computation tree f ..."
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Cited by 31 (22 self)
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this paper we assume that a system makes transitions from states to states and its evolution can be formalized using a computation tree which is dened as follows. Given a system S and its initial state s 0 , the root of the computation tree for S is s 0 , and every node s i of the computation tree for S has a child node s j i there exists in S a transition from state s i to state s j , called a successor state of s i . The set of all states of a system may be nite or innite. We assume that in every system for every state s i there exists at least one successor state
Reducing Nondeterminism while Specializing Logic Programs
, 1997
"... Program specialization is a collection of program transformation techniques for improving program efficiency by exploiting some information available at compiletime about the input data. We show that current techniques for program specialization based on partial evaluation do not perform well on non ..."
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Cited by 27 (15 self)
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Program specialization is a collection of program transformation techniques for improving program efficiency by exploiting some information available at compiletime about the input data. We show that current techniques for program specialization based on partial evaluation do not perform well on nondeterministic logic programs. We then consider a set of transformation rules which extend the ones used for partial evaluation, and we propose a strategy to direct the application of these extended rules so to derive very efficient specialized programs. The efficiency improvements which may even be exponential, are achieved because the derived programs are semideterministic and the operations which are performed by the initial programs in different branches of the computation trees, are performed in the specialized programs within single branches. We also make use of mode information to guide the unfolding process and to reduce nondeterminism. To exemplify our technique, we show that we can...
A Comparative Revisitation of Some Program Transformation Techniques
 Partial Evaluation, Int'l Seminar, Dagstuhl
, 1996
"... . We revisit the main techniques of program transformation which are used in partial evaluation, mixed computation, supercompilation, generalized partial computation, rulebased program derivation, program specialization, compiling control, and the like. We present a methodology which underlines the ..."
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Cited by 21 (0 self)
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. We revisit the main techniques of program transformation which are used in partial evaluation, mixed computation, supercompilation, generalized partial computation, rulebased program derivation, program specialization, compiling control, and the like. We present a methodology which underlines these techniques as a `common pattern of reasoning' and explains the various correspondences which can be established among them. This methodology consists of three steps: i) symbolic computation, ii) search for regularities, and iii) program extraction. We also discuss some control issues which occur when performing these steps. 1 Introduction During the past years researchers working in various areas of program transformation, such as partial evaluation, mixed computation, supercompilation, generalized partial computation, rulebased program derivation, program specialization, and compiling control, have been using very similar techniques for the development and derivation of programs. Unfor...
Metaprogramming Forced Moves
 Proceedings of the 13th European Conference on Artificial Intelligence (ECAI'98
, 1998
"... . Knowledge about forced moves enables to select a small number of moves from the set of possible moves. It is very important in complex domains where search trees have a large branching factor. Knowing forced moves drastically cuts the search trees. We propose a language and a metaprogram to create ..."
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Cited by 10 (4 self)
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. Knowledge about forced moves enables to select a small number of moves from the set of possible moves. It is very important in complex domains where search trees have a large branching factor. Knowing forced moves drastically cuts the search trees. We propose a language and a metaprogram to create automatically the knowledge about interesting and forced moves, only given the rules about the direct effects of the moves. We describe the successful application of this metaprogram to the game of Go. It creates rules that give complete sets of forced moves. 1 INTRODUCTION Knowledge about forced moves enables to select a small number of moves from the set of possible moves. It is very important in complex domains where search trees have a large branching factor. Knowing forced moves drastically cuts the search trees. We propose a language and a metaprogram to create automatically the knowledge about interesting and forced moves, only given the rules about the direct effects of the moves. ...
Enhancing Partial Deduction via Unfold/Fold Rules
 Proc. LoPSTr '96
, 1996
"... We show that sometimes partial deduction produces poor program specializations because of its limited ability in (i) dealing with conjunctions of recursively defined predicates, (ii) combining partial evaluations of alternative computations, and (iii) taking into account unification failures. We pro ..."
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Cited by 7 (4 self)
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We show that sometimes partial deduction produces poor program specializations because of its limited ability in (i) dealing with conjunctions of recursively defined predicates, (ii) combining partial evaluations of alternative computations, and (iii) taking into account unification failures. We propose to extend the standard partial deduction technique by using versions of the definition rule and the folding rule which allow us to specialize predicates defined by disjunctions of conjunctions of goals. We also consider a case split rule to take into account unification failures. Moreover, in order to perform program specialization via partial deduction in an automatic way, we propose a transformation strategy which takes as parameters suitable substrategies for directing the application of every transformation rule. Finally, we show through two examples that our partial deduction technique is superior to standard partial deduction. The first example refers to the automatic derivation...
Rules and Strategies for Contextual Specialization of Constraint Logic Programs
 Electronic Notes in Theoretical Computer Science 30(2
, 2000
"... We address the problem of specializing a constraint logic program w.r.t. a constrained atom which specifies the context of use of the program. We follow an approach based on transformation rules and strategies. We introduce a novel transformation rule, called contextual constraint replacement, to be ..."
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Cited by 4 (2 self)
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We address the problem of specializing a constraint logic program w.r.t. a constrained atom which specifies the context of use of the program. We follow an approach based on transformation rules and strategies. We introduce a novel transformation rule, called contextual constraint replacement, to be combined with variants of the traditional unfolding and folding rules. We present a general Partial Evaluation Strategy for automating the application of these rules, and two additional strategies: the Context Propagation Strategy which is instrumental for the application of our contextual constraint replacement rule, and the Invariant Promotion Strategy for taking advantage of invariance properties of the computation. We show through some examples the power of our method and we compare it with existing methods for partial deduction of constraint logic programs based on extensions of Lloyd and Shepherdson's approach.