The use of mathematical models in biomedical research largely developed in the second half of the 20th century. However, their translation to clinically useful tools has proved challenging. Reasoning with deep biomedi...
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ISBN:
(纸本)9783319234854;9783319234847
The use of mathematical models in biomedical research largely developed in the second half of the 20th century. However, their translation to clinically useful tools has proved challenging. Reasoning with deep biomedical models is computationally demanding as parameters are typically subject to nonlinear relations, dynamic behavior, and uncertainty. This paper proposes a new approach for assessing the reliability of the conclusions drawn from these models given the underlying uncertainty. It relies on probabilistic constraint programming for a sound propagation of uncertainty from model parameters to results. The advantages of the approach are illustrated on an important problem in the obesity research field, namely the estimation of free-living energy intake in humans. Based on a well known energy intake model, our approach is able to correctly characterize the provided estimates given the uncertainty inherent to the model parameters.
constraint Satisfaction Problems allow one to expressively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to expressive...
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constraint Satisfaction Problems allow one to expressively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to expressively model set constraint problems and to encode them automatically into SAT instances. Our technique is expressive and less error-prone. We apply it to the Social Golfer Problem and to symmetry breaking of the problem.
The maximum common subgraph problem is an NP-hard problem which is very difficult to solve with exact approaches. To speed up the solution process, we may decompose it into independent subproblems which are solved in ...
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ISBN:
(纸本)9781509001637
The maximum common subgraph problem is an NP-hard problem which is very difficult to solve with exact approaches. To speed up the solution process, we may decompose it into independent subproblems which are solved in parallel. We describe a new decomposition method which exploits the structure of the problem to decompose it. We compare this structural decomposition with domain-based decompositions, which basically split variable domains. Experimental results show us that the structural decomposition leads to better speedups on two classes of instances, and to worse speedups on one class of instances.
This paper introduces the ongoing work for a novel domain-independent planning system which takes inspiration from both constraint programming (CP) and Logic programming (LP), flavouring it all with Object Oriented fe...
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ISBN:
(纸本)9783319243092;9783319243085
This paper introduces the ongoing work for a novel domain-independent planning system which takes inspiration from both constraint programming (CP) and Logic programming (LP), flavouring it all with Object Oriented features. We will see a specific customization of our environment to the particular kind of automated planning referred to as timeline-based. By allowing for the interesting ability of solving both planning and scheduling problems in a uniform schema, the resulting system is particularly suitable for complex domains arising from real dynamic scenarios. The paper proposes a resolution algorithm and enhances it with some (static and dynamic) heuristics to help the solving process. The system is tested on different benchmark problems from classical planning domains like the Blocks World to more challenging temporally expressive problems like the Temporal Machine Shop and the Cooking Carbonara problems demonstrating how the new planner, named iLoC, compares with respect to other state-of-the-art planners.
constraint programming allows to solve constraint satisfaction and optimization problems by building and then exploring a search tree of potential solutions. Potential solutions are generated by firstly selecting a va...
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ISBN:
(纸本)9783319188331;9783319188324
constraint programming allows to solve constraint satisfaction and optimization problems by building and then exploring a search tree of potential solutions. Potential solutions are generated by firstly selecting a variable and then a value from the given problem. The enumeration strategy is responsible for selecting the order in which those variables and values are selected to produce a potential solution. There exist different ways to perform this selection, and depending on the quality of this decision, the efficiency of the solving process may dramatically vary. A modern idea to handle this concern, is to interleave during solving time a set of different strategies instead of using a single one. The strategies are evaluated according to process indicators in order to use the most promising one on each part of the search process. This process is known as online control of enumeration strategies and its correct configuration can be seen itself as an optimization problem. In this paper, we present a new system for online control of enumeration strategies based on bat-inspired optimization. The bat algorithm is a relatively modern metaheuristic based on the location behavior of bats that employ echoes to identify the objects in their surrounding area. We illustrate, promising results where the proposed bat algorithm is able to outperform previously reported metaheuristic-based approaches for online control of enumeration strategies.
In constraint programming, efficiency in the resolution process can be affected by the order in which the variables of the problem and the domain values are selected. This activity is known as enumeration. At the begi...
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ISBN:
(纸本)9781479983308
In constraint programming, efficiency in the resolution process can be affected by the order in which the variables of the problem and the domain values are selected. This activity is known as enumeration. At the beginning, it is difficult to determine the best choice variable-value pair that can generate potential solutions for constraint satisfaction problems. In this paper, we present an evaluation of different enumeration strategies, based on performance exhibited in a set indicators. These strategies solve different instances of constraint problems satisfactions. The results show that it is feasible to solve constraint satisfaction with at least one strategy enumeration.
Complex event processing is key technology for current business in which sequences of events are controlled. However, defining complex events is not easy, and sequence learning algorithms can help. To that end, sequen...
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ISBN:
(纸本)9781509002870
Complex event processing is key technology for current business in which sequences of events are controlled. However, defining complex events is not easy, and sequence learning algorithms can help. To that end, sequence learning methods should consider temporal relationship among events. In this paper, we tackle the problem of mining complex events using frequent sequence pattern mining with time gaps. A constraint model of the learning problem is proposed. Consistently, the learning problem is addressed using solvers off the shelf. The experiments are carried out in a bike hiring domain so as a CEP system can account how many users will reach a depot, independently of which was their origin. Results are analysed in terms of individual and multiple users, as well as regarding the scalability of the method.
Testing a telecommunication protocol often requires protocol log analysis. A protocol log is a sequence of messages with timestamps. Protocol log analysis involves checking that the content of messages and timestamps ...
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ISBN:
(数字)9783319212159
ISBN:
(纸本)9783319212159;9783319212142
Testing a telecommunication protocol often requires protocol log analysis. A protocol log is a sequence of messages with timestamps. Protocol log analysis involves checking that the content of messages and timestamps are correct with respect to the protocol specification. We model a protocol specification using constraint programming (MiniZinc), and we present an approach where a constraint solver is used to perform protocol log analysis. Our case study is the Public Warning System service, which is a part of the Long Term Evolution (LTE) 4G standard. We were able to analyse logs containing more than 3000 messages with more than 4000 errors.
Performance analysis and tuning are well established software engineering processes in the realm of imperative programming. This work is a step towards establishing the standards of performance analysis in the realm o...
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constraint-based search techniques have gained increasing attention in recent years as a basis for scheduling procedures that are capable of accommodating a wide range of constraints. Among these, the Large Neighborho...
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ISBN:
(纸本)9783319184227;9783319184210
constraint-based search techniques have gained increasing attention in recent years as a basis for scheduling procedures that are capable of accommodating a wide range of constraints. Among these, the Large Neighborhood Search (LNS) has largely proven to be a very effective heuristic-based methodology. Its basic optimization cycle consists of a continuous iteration of two steps where the solution is first relaxed and then re-constructed. In constraint programming terms, relaxing entails the retraction of some previously imposed constraints, while re-constructing entails imposing new constraints, searching for a better solution. Each iteration of constraint removal and re-insertion can be considered as the examination of a large neighborhood move, hence the procedure's name. Over the years, LNS has been successfully employed over a wide range of different problems;this paper intends to provide an overview of some utilization examples that demonstrate both the versatility and the effectiveness of the procedure against significantly difficult scheduling benchmarks known in literature.
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