Titlebook: Logic Programming; 25th International C Patricia M. Hill,David S. Warren Conference proceedings 2009 Springer-Verlag Berlin Heidelberg 2009

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坚毅

(C)LP Tracing and Debuggingor (constraint) logic programming. The tutorial presents trace production techniques, ranging from compiler instrumentations to dedicated meta-interpreters. It reviews work on trace analysis, in particular algorithmic, declarative and rational debugging. It discusses the issue of trace querying and

Cirrhosis

Probabilistic Logic Learning - A Tutorial Abstractigence: the integration of probabilistic reasoning with first order logic representations and machine learning. It has received a lot of attention recently and a rich variety of different formalisms and learning techniques have been developed, which are now being applied to applications in network a

Generic-Drug

Using Histograms to Better Answer Queries to Probabilistic Logic Programsrlying logical language. When answering a query ., a lower and upper bound on . is obtained by optimizing (min and max) an objective function subject to a set of linear constraints whose solutions are the PDFs mentioned above. A common critique not only of PLPs but many probabilistic logics is that

Aspiration

Non-discriminating Arguments and Their Usessatisfying given mode and sharing restrictions. We call such arguments . arguments. We show that such arguments can be detected by an automatic analysis. Following this, we define a transformation procedure, called ., that removes the non-discriminating arguments, resulting in a program whose comput

范围广

Preprocessing for Optimization of Probabilistic-Logic Models for Sequence Analysisn principle, Turing complete languages. In general, such models are computationally far too complex for direct use, so optimization by pruning and approximation are needed. The first steps are taken towards a methodology for optimizing such models by approximations using auxiliary models for preproc

BROTH

Stabilization of Information Sharing for Queries Answering in Multiagent Systemsent could sense or receive from other agents, must cooperate to provide answers to users as they may not have the knowledge or the capabilities to sense relevant changes in their environment. As their surroundings may change unpredictably, agents may provide wrong answers to queries. Stabilization r

争吵加

Logic Programming for Multiagent Planning with Negotiationate, in order to achieve their goals. One way for the agents to interact is through negotiations. Integration of negotiation in multiagent planning has not been extensively investigated and a systematic way for this task has yet to be found. We develop a generic model for negotiation in dynamic envi

Vulnerable

Answer Set Programming with Constraints Using Lazy Groundingat does not require a preliminary grounding phase. The implementation of the framework can be completely realized within the framework of Constraint Logic Programming over finite domains. The use of a high level language for the implementation and the clean structure of the computation offer an idea

caldron

Computing Loops with at Most One External Support Rule for Disjunctive Logic Programse logic programs, loop formulas of loops with no external support can be computed in polynomial time, and if the given program has no constraints, an iterative procedure based on these formulas, the program completion, and unit propagation computes the least fixed point of a simplification operator