Download presentation

Presentation is loading. Please wait.

Published byIngrid Bassham Modified about 1 year ago

1
Introduction

2
IC-Parc2 ECLiPSe Components Constraint Logic Programming system, consisting of A runtime core Data-driven computation, backtracking, garbage collection A collection of libraries Constraint propagators, search support, application support, development support A modelling and control language Logic programming A development environment Tkeclipse Interfaces for embedding into host environments Java, Tcl/Tk, C/C++ Interfaces to third-party solvers Xpress-MP, Cplex, COIN-OR Constraint Logic Programming system, consisting of A runtime core Data-driven computation, backtracking, garbage collection A collection of libraries Constraint propagators, search support, application support, development support A modelling and control language Logic programming A development environment Tkeclipse Interfaces for embedding into host environments Java, Tcl/Tk, C/C++ Interfaces to third-party solvers Xpress-MP, Cplex, COIN-OR

3
IC-Parc3 ECLiPSe Uses ECLiPSe is intended for General programming tasks especially rapid prototyping Problem solving using the CLP paradigm using the available solver libraries Development of new constraint solvers employing ECLiPSe's lower-level language features possibly based on the existing solvers ECLiPSe is intended for General programming tasks especially rapid prototyping Problem solving using the CLP paradigm using the available solver libraries Development of new constraint solvers employing ECLiPSe's lower-level language features possibly based on the existing solvers

4
IC-Parc4 How Does It Work - The C(L)P Paradigm Model Heuristics Search Efficient Algorithms Efficient Algorithms Xi Cj

5
IC-Parc5 Constraint (Logic) Programming Program = Logic + Control Control = Reasoning + Search Declarative Problem model Constraint propagation Clever algorithms Heuristics Problem specific knowledge

6
IC-Parc6 Why use Logic Programming and Prolog? Predicates over logical variables Constraints over mathematical variables (unlike ‘variable’ = storage location as in imperative languages!) Program = Logic + Control Solution = Model + Solver Symbolic manipulation and metaprogramming Program/data interchangeability is good for implementing solvers, programming search, preprocessing constraints, etc Built-in backtracking A general default mechanism for handling disjunctions A convenient primitive for programming more complex search

7
IC-Parc7 Constraint Program Template :- lib(...). solve(Variables) :- setup_constraints(Variables), search(Variables). :- lib(...). solve(Variables) :- setup_constraints(Variables), search(Variables). Model deterministic correctness Search nondeterministic choices & heuristics efficiency Algorithms deterministic efficiency

8
IC-Parc8 Logic Programming for Modelling Variables can have attributes e.g. domain, type Constraints = predicates, involving 1 or more variables Model = setup program X1{1..9} alldifferent([ _, _, _ ]) X3{5..9} X2{3..9} X4{1..7} _ #> _ _ #\= _ [X1,X2,X3,X4]::1..9, X1 #> X2, alldifferent([X2,X3,X4]), X1 #\= X4.

9
IC-Parc9 Logic Programming for Search Binary choice ( X=0 ; X=1 ) Enumerate ( X=1 ; X=2 ; X=3 ; X=4 ) X :: 1..4, indomain(X) Split ( X #= 5 ) Heuristic choice ( X = Guess ; X #\= Guess )

10
IC-Parc10 Related Languages Formal specification languages (e.g. B, Z, VDM) More expressive power than ECLiPSe, but not executable Mathematical modelling languages (e.g. OPL, AMPL) Similar to ECLiPSe, but usually limited expressive power (e.g. fixed set of constraints) and limited control Search languages (Salsa, ToOls) For expressing search strategies, special-purpose Mainstream programming languages (e.g. C++ with ILOG) Variables and constraints are “aliens” in the language Specification mixed up with procedural control Other CLP/high-level languages (e.g. CHIP, SICStus, Oz) Most similar to ECLiPSe. Less support for hybrid problem solving. Harder to define new constraints Formal specification languages (e.g. B, Z, VDM) More expressive power than ECLiPSe, but not executable Mathematical modelling languages (e.g. OPL, AMPL) Similar to ECLiPSe, but usually limited expressive power (e.g. fixed set of constraints) and limited control Search languages (Salsa, ToOls) For expressing search strategies, special-purpose Mainstream programming languages (e.g. C++ with ILOG) Variables and constraints are “aliens” in the language Specification mixed up with procedural control Other CLP/high-level languages (e.g. CHIP, SICStus, Oz) Most similar to ECLiPSe. Less support for hybrid problem solving. Harder to define new constraints

11
IC-Parc11 Components Covered in this Course ECLiPSe Programming language Constraint Solver Libraries e.g. ic, eplex, ic_global, ic_sets, ic_symbolic, suspend Search & Optimization Support Libraries e.g. ic_search, branch_and_bound, repair Constraint Building Support Libraries e.g. propia, chr/ech General Programming Support Libraries e.g. lists, hash, … Development Tools e.g. tkeclipse, visualisation, coverage, profile, document

12
IC-Parc12 Constraint Solver Libraries Solver library Variable domains Constraints classBehaviour suspend numericArbitrary arithmetic in/dis/equalitiesPassive test fd integer, symbol Linear in/dis/equalities and some others Domain propagation ic real, integerArbitrary arithmetic in/dis/equalities Bounds/domain propagation ic_global integer N-ary constraints over lists of integers Bounds/domain propagation ic_sets set of integer Set operations (subset, cardinality, union, …) Set-bounds propagation ic_symbolic ordered symbolsDis/equality, ordering, element, … Bounds/domain propagation propia inheritedanyvarious eplex real, integerLinear in/equalitiesGlobal, optimising

Similar presentations

© 2016 SlidePlayer.com Inc.

All rights reserved.

Ads by Google