Stable Models for the Distribution of Capital

2002 ◽  
pp. 93-118
Author(s):  
E. Robert Fernholz
Keyword(s):  
Stable Models

scholarly journals Understanding the Traffic Nature of Mobile Instantaneous Messaging in Cellular Networks: A Revisiting to $\alpha $ -Stable Models

IEEE Access ◽  
2015 ◽  
Vol 3 ◽  
pp. 1416-1422 ◽  
Author(s):  
Rongpeng Li ◽  
Zhifeng Zhao ◽  
Chen Qi ◽  
Xuan Zhou ◽  
Yifan Zhou ◽  
...  
Keyword(s):  
Cellular Networks ◽  
Stable Models

Unsatisfiable Core Analysis and Aggregates for Optimum Stable Model Search

2020 ◽  
Vol 176 (3-4) ◽  
pp. 271-297
Author(s):  
Mario Alviano ◽  
Carmine Dodaro
Keyword(s):  
State Of The Art ◽  
Answer Set Programming ◽  
Efficient Algorithms ◽  
Satisfiability Problem ◽  
Core Analysis ◽  
Stable Model ◽  
Maximum Satisfiability ◽  
Model Search ◽  
Unsatisfiable Core ◽  
Stable Models

Many efficient algorithms for the computation of optimum stable models in the context of Answer Set Programming (ASP) are based on unsatisfiable core analysis. Among them, algorithm OLL was the first introduced in the context of ASP, whereas algorithms ONE and PMRES were first introduced for solving the Maximum Satisfiability problem (MaxSAT) and later on adapted to ASP. In this paper, we present the porting to ASP of another state-of-the-art algorithm introduced for MaxSAT, namely K, which generalizes ONE and PMRES. Moreover, we present a new algorithm called OLL-IN-ONE that compactly encodes all aggregates of OLL by taking advantage of shared aggregate sets propagators. The performance of the algorithms have been empirically compared on instances taken from the latest ASP Competition.

The interpretation of unsolvable λ-terms in models of untyped λ-calculus

1998 ◽  
Vol 63 (4) ◽  
pp. 1529-1548 ◽  
Author(s):  
Rainer Kerth
Keyword(s):  
Graph Model ◽  
Stable Model ◽  
Graph Models ◽  
Stable Models

AbstractOur goal in this paper is to analyze the interpretation of arbitrary unsolvable λ-terms in a given model of λ-calculus. We focus on graph models and (a special type of) stable models. We introduce the syntactical notion of a decoration and the semantical notion of a critical sequence. We conjecture that any unsolvable term β-reduces to a term admitting a decoration. The main result of this paper concerns the interconnection between those two notions: given a graph model or stable model , we show that any unsolvable term admitting a decoration and having a non-empty interpretation in generates a critical sequence in the model.In the last section, we examine three classical graph models, namely the model of Plotkin and Scott, Engeler's model and Park's model . We show that and do not contain critical sequences whereas does.

Stable Models in Testable Asset Pricing

1994 ◽  
pp. 223-235 ◽  
Author(s):  
Bertrand Gamrowski ◽  
Svetlozar T. Rachev
Keyword(s):  
Asset Pricing ◽  
Stable Models

scholarly journals Greedy algorithms in Datalog

2001 ◽  
Vol 1 (4) ◽  
pp. 381-407 ◽  
Author(s):  
SERGIO GRECO ◽  
CARLO ZANIOLO
Keyword(s):  
Optimization Problems ◽  
Greedy Algorithms ◽  
Design Of Algorithms ◽  
Effective Implementation ◽  
Implementation Techniques ◽  
Research Challenge ◽  
Storage Structures ◽  
Selection Of ◽  
Stable Models

In the design of algorithms, the greedy paradigm provides a powerful tool for solving efficiently classical computational problems, within the framework of procedural languages. However, expressing these algorithms within the declarative framework of logic-based languages has proven a difficult research challenge. In this paper, we extend the framework of Datalog-like languages to obtain simple declarative formulations for such problems, and propose effective implementation techniques to ensure computational complexities comparable to those of procedural formulations. These advances are achieved through the use of the choice construct, extended with preference annotations to effect the selection of alternative stable-models and nondeterministic fixpoints. We show that, with suitable storage structures, the differential fixpoint computation of our programs matches the complexity of procedural algorithms in classical search and optimization problems.

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