摘要 :
The purpose of this study is to develop a multidimensional measure of consumer-based leisure constraint for online game play and to assess its psychometric properties. An empirical model of player constraint in online games provid...
展开
The purpose of this study is to develop a multidimensional measure of consumer-based leisure constraint for online game play and to assess its psychometric properties. An empirical model of player constraint in online games provides the foundation to understanding and assessing how players differ from one another (such as high gamers/low gamers and high gamers/non-gamers) and how constraints on play relate to frequency of use. In the current study, an exploratory factor analysis was used to extract the common factors, and confirmatory factor analysis was used to create an empirical model of players' perception of constraint and to reveal its underlying structure. The analysis revealed six dimensions of constraint. The relationship between perception of constraint and frequency of use is also presented.
收起
摘要 :
Soft constraints are a generalization of classical constraints, which allow for the description of preferences rather than strict requirements. In soft constraints, constraints and partial assignments are given preference or impor...
展开
Soft constraints are a generalization of classical constraints, which allow for the description of preferences rather than strict requirements. In soft constraints, constraints and partial assignments are given preference or importance levels, and constraints are combined according to combinators which express the desired optimization criteria. On the other hand, constraint handling rules (CHR) constitute a high-level natural formalism to specify constraint solvers and propagation algorithms. We present a framework to design and specify soft constraint solvers by using CHR. In this way, we extend the range of applicability of CHR to soft constraints rather than just classical ones, and we provide a straightforward implementation for soft constraint solvers.
收起
摘要 :
One-way, dataflow constraints are commonly used in graphical interface toolkits, programming en- vironments, and circuit applications. Previous papers on dataflow constraints have focused on the design and implementation of indivi...
展开
One-way, dataflow constraints are commonly used in graphical interface toolkits, programming en- vironments, and circuit applications. Previous papers on dataflow constraints have focused on the design and implementation of individual algorithms. In contrast, this article focuses on the lessons we have learned from a decade of implementing competing algorithms in the Garnet and Amulet graphical interface toolkits. These lessons reveal the design and implementation tradeoffs for dif- ferent one-way, constraint satisfaction algorithms.
收起
摘要 :
Research on constraints started in the early 1970s. We are approaching 40 years since the beginning of this successful field, and it is an opportunity to revise what has been reached. This paper is a personal view of the accomplis...
展开
Research on constraints started in the early 1970s. We are approaching 40 years since the beginning of this successful field, and it is an opportunity to revise what has been reached. This paper is a personal view of the accomplishments in this field. We summarize the main achievements along three dimensions: constraint solving, modelling and programming. We devote special attention to constraint solving, covering popular topics such as search, inference(especially arc consistency), combination of search and inference, symmetry exploitation, global constraints and extensions to the classical model. For space reasons, several topics have been deliberately omitted.
收起
摘要 :
Open forms of global constraints allow the addition of new variables to an argument during the execution of a constraint program. Such forms are needed for difficult constraint programming problems, where problem construction and ...
展开
Open forms of global constraints allow the addition of new variables to an argument during the execution of a constraint program. Such forms are needed for difficult constraint programming problems, where problem construction and problem solving are interleaved, and fit naturally within constraint logic programming. However, in general, filtering that is sound for a global constraint can be unsound when the constraint is open. This paper provides a simple characterization, called contractibility, of the constraints, where filtering remains sound when the constraint is open. With this characterization, we can easily determine whether a constraint has this property or not. In the latter case, we can use it to derive a contractible approximation to the constraint. We demonstrate this work on both hard and soft constraints. In the process, we formulate two general classes of soft constraints.
收起
摘要 :
Constraint Optimization Problems (COPs) ask for an assignment of values to variables in order to optimize an objective subject to constraints that restrict the value combinations in the assignment. They are usually solved by the c...
展开
Constraint Optimization Problems (COPs) ask for an assignment of values to variables in order to optimize an objective subject to constraints that restrict the value combinations in the assignment. They are usually solved by the classical Branch and Bound (B&B) search algorithm. Dominance breaking is an important technique in B&B to prune assignments that are subordinate to others concerning the objective value and/or the satisfiability of constraints. In practice, the addition of constraints for dominance breaking can drastically speed up the B&B search for solving many COPs. However, identification of suboptimal assignments in COPs and derivation of useful constraints for dominance breaking are usually problem-specific and require sophisticated human insights on the problem structure.This paper proposes the first theoretical and practical framework for automatic generation of dominance breaking constraints for a class of COPs consisting of eficiently checkable objectives and constraints. In particular, the framework focuses on generating nogood constraints representing incompatible value assignments and formulates nogood generation as solving auxiliary constraint satisfaction problems. The proposed method can generate nogoods of varying strengths for dominance breaking by controlling the number of involved variables. Experimentation on various benchmarks demonstrates the effectiveness of the proposal in both efficiency and ease of use. The superior performance is also supported by a theoretical analysis to compare the relative strength of automatically generated nogoods with manually derived dominance breaking constraints in the literature.
收起
摘要 :
Dominance constraints are a language of tree descriptions. Tree descriptions are widely used in computational linguistics for talking and reasoning about trees. While previous research has focused on the conjunctive fragment, we n...
展开
Dominance constraints are a language of tree descriptions. Tree descriptions are widely used in computational linguistics for talking and reasoning about trees. While previous research has focused on the conjunctive fragment, we now extend the account to all Boolean connectives and propose a new formalism that combines dominance constraints with a feature tree logic. Although the satisfiability problem in the conjunctive fragment is known to be NP-complete, we have previously demonstrated that it can be addressed very effectively by constraint propagation: we developed an encoding that transforms a dominance constraint into a constraint satisfaction problem on finite sets solvable by constraint programming. We present a generalization of this encoding for our more expressive formalism, and prove soundness and completeness. Our main contribution is a treatment of disjunction suitable for constraint propagation.
收起
摘要 :
Mean-variance optimization often leads to unreasonable asset allocations. This problem has forced scholars and practitioners alike to introduce portfolio constraints. The scope of our study is to verify which type of constraint is...
展开
Mean-variance optimization often leads to unreasonable asset allocations. This problem has forced scholars and practitioners alike to introduce portfolio constraints. The scope of our study is to verify which type of constraint is more suitable for achieving efficient performance. We have applied the main techniques developed by the financial community, including classical weight, flexible, norm-based, variance-based, tracking error volatility, and beta constraints. We employed panel data on the monthly returns of the sector indices forming the MSCI All Country World Index from January 1995 to December 2020. The assessment of each strategy was based on out-of-sample performance, measured using a rolling window method with annual rebalancing. We observed that the best strategies are those subject to constraints derived from the equal-weighted model. If the goal is the best compromise between absolute return, efficiency, total risk, economic sustainability, diversification, and ease of implementation, the best solution is a portfolio subject to no short selling and bound either to the equal weighting or to TEV limits. Overall, we found that constrained optimization models represent an efficient alternative to classic investment strategies that provide substantial advantages to investors.
收起
摘要 :
Substitutability and interchangeability in constraint satisfaction problems (CSPs) have been used as a basis for search heuristics, solution adaptation and abstraction techniques. In this paper, we consider how the same concepts c...
展开
Substitutability and interchangeability in constraint satisfaction problems (CSPs) have been used as a basis for search heuristics, solution adaptation and abstraction techniques. In this paper, we consider how the same concepts can be extended to soft constraint satisfaction problems (SCSPs). We introduce two notions: threshold α and degradation factor δ for substitutability and interchangeability, ( α substitutability/interchangeability and δ substitutability/interchangeabi-lity respectively). We show that they satisfy analogous theorems to the ones already known for hard constraints. In α interchangeability, values are interchangeable in any solution that is better than a threshold α, thus allowing to disregard differences among solutions that are not sufficiently good anyway. In δ interchangeability, values are interchangeable if their exchange could not degrade the solution by more than a factor of δ. We give efficient algorithms to compute ( δ / α )interchangeable sets of values for a large class of SCSPs, and show an example of their application. Through experimental evaluation based on random generated problem we measure first, how often neighborhood interchangeable values are occurring, second, how well they can approximate fully interchangeable ones, and third, how efficient they are when used as preprocessing techniques for branch and bound search.
收起
摘要 :
Substitutability and interchangeability in constraint satisfaction problems (CSPs) have been used as a basis for search heuristics, solution adaptation and abstraction techniques. In this paper, we consider how the same concepts c...
展开
Substitutability and interchangeability in constraint satisfaction problems (CSPs) have been used as a basis for search heuristics, solution adaptation and abstraction techniques. In this paper, we consider how the same concepts can be extended to soft constraint satisfaction problems (SCSPs). We introduce two notions: threshold α and degradation factor δ for substitutability and interchangeability, (_αsubstitutability/interchangeability and ~δsubstitutability/interchangeabi-lity respectively). We show that they satisfy analogous theorems to the ones already known for hard constraints. In _αinterchangeability, values are interchangeable in any solution that is better than a threshold α, thus allowing to disregard differences among solutions that are not sufficiently good anyway. In ~δ interchangeability, values are interchangeable if their exchange could not degrade the solution by more than a factor of δ. We give efficient algorithms to compute (~δ/α interchangeable sets of values for a large class of SCSPs, and show an example of their application. Through experimental evaluation based on random generated problem we measure first, how often neighborhood interchangeable values are occurring, second, how well they can approximate fully interchangeable ones, and third, how efficient they are when used as preprocessing techniques for branch and bound search.
收起
原文获取