Although propagation techniques are very important to solve constraint solving problems, heuristics are still necessary to handle non trivial problems efficiently. General principles may be defined for such heuristics...
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ISBN:
(纸本)3540232370
Although propagation techniques are very important to solve constraint solving problems, heuristics are still necessary to handle non trivial problems efficiently. General principles may be defined for such heuristics (e.g. first-fail and best-promise), but problems arise in their implementation except for some limited sources of information (e.g. cardinality of variables domain). Other possibly relevant features are ignored due to the difficulty in understanding their interaction and a convenient way of integrating them. In this paper we illustrate such difficulties in a specific problem, determination of protein structure from Nuclear Magnetic Resonance (NMR) data. We show that machine learning techniques can be used to define better heuristics than the use of heuristics based on single features, or even than their combination in simple form (e.g majority vote). The technique is quite general and, with the necessary adaptations, may be applied to many other constraint satisfaction problems.
This paper describes a new programming system for writing web applications with reactive agents, i.e. the agents can have complex responses which depend on how the environment changes. Our prototype system is based on...
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ISBN:
(纸本)0769510655
This paper describes a new programming system for writing web applications with reactive agents, i.e. the agents can have complex responses which depend on how the environment changes. Our prototype system is based on the Open constraint programming framework using the constraint Logic programming language CLP(R). The benefit of reactive web agents is that activities of agents can be coordinated and synchronized using a common stove and the agents can themselves be written as a system of interacting rules. Our thesis is that such a system makes it easy to write powerful reactive applications. We use a stock trading system to illustrate our reactive agents. Some details of the implementation are also given.
A hybrid framework that uses Mathematical and constraint programming for the scheduling of batch chemical processes is proposed. Mathematical programming is used for the high-level optimization decisions (number and t...
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We combine mixed integer linear programming (MILP) and constraint programming (CP) to solve planning and scheduling problems. Tasks are allocated to facilities using MILP and scheduled using CP, and the two are linked...
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We introduce a new global constraint for modeling and solving network flow problems in constraint programming. We describe the declarative and operational semantics of the flow constraint and illustrate its use throug...
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In organizations where duty is around the clock, seven days a week and every week of the year, timetabling is a very difficult task, juggling between the workload and the constraints to be respected. Our work concerns...
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ISBN:
(纸本)3540424210
In organizations where duty is around the clock, seven days a week and every week of the year, timetabling is a very difficult task, juggling between the workload and the constraints to be respected. Our work concerns cyclical timetabling. This is not just duplicating a fixed sequence of assignments, but has to consider fixed annual leave, and various regulations on assignments on successive days. In some cases, the cycle sequence has to be relaxed and cycle length shortened or extended. In other cases, a small change in leave dates is allowed, except in summer. This paper describes the context and the use of work cycles in the real world, proposes an abstract model to take into account the various constraints, and finally shows how to implement an effective solution using constraint logic programming (in particular, CHIP V5) to produce timetables of up to 150 people over a yearly horizon.
We present Branch-and-Check, a hybrid framework integrating Mixed Integer programming and constraint Logic programming, which encapsulates the traditional Benders Decomposition and Branch-and-Bound as special cases. I...
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Benders Decomposition is a form of hybridisation that allows linear programming to be combined with other kinds of algorithms. It extracts new constraints for one subproblem from the dual values of the other subproble...
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programming complex embedded systems involves reasoning through intricate system interactions along lengthy paths between sensors, actuators, and control processors. This is a challenging, time-consuming, and error-pr...
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programming complex embedded systems involves reasoning through intricate system interactions along lengthy paths between sensors, actuators, and control processors. This is a challenging, time-consuming, and error-prone process requiring significant interaction between engineers and software programmers. Furthermore, the resulting code generally lacks. modularity and robustness in the presence of failure. Model-based programming addresses these limitations, allowing engineers to program reactive systems by specifying high-level control strategies and by assembling commonsense models of the system hardware and software. In executing a control strategy, model-based executives reason about the models "on the fly, " to track system state, diagnose faults, and perform reconfigurations. This paper develops the Reactive Model-Based programming Language (RMPL) and its executive, called Titan. RMPL provides the features of synchronous, reactive languages, with the added ability of reading and writing to state variables that are hidden within the physical plant being controlled. Titan executes an RMPL program using extensive component-based declarative models of the plant to track states, analyze anomalous situations, and generate novel control sequences. Within its reactive control loop, Titan employs propositional inference to deduce the system's current and desired states, and it employs model-based reactive planning to move the plant from the current to the desired state.
This paper suggests a method that utilizes non-real time information as an aid to improve maritime surveillance. Under certain conditions vessels move in accordance with preplanned routes and possibly also report thei...
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This paper suggests a method that utilizes non-real time information as an aid to improve maritime surveillance. Under certain conditions vessels move in accordance with preplanned routes and possibly also report their own position at certain positions or at certain times during the voyage. The method proposed consists of a statistical route model that describes the movement of the vessel, and includes refinement of the estimated movement based upon reports on the vessel. The estimated movement is then associated with radar tracks using multiple hypothesis techniques. This is due to the fact that the number of vessels with known route plans is small compared to the total number of vessels in an area. The associated radar tracks are also used to improve the estimated movement of the vessels. The problem of generating possible solutions and selecting the best hypothesis is formulated as a constraint satisfaction problem and implemented using a constraint programming technique.
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