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24
Planning with preferences using logic programming
, 2006
"... We present a declarative language,PP, for the highlevel specification of preferences between possible solutions (or trajectories) of a planning problem. This novel language allows users to elegantly express nontrivial, multidimensional preferences and priorities over such preferences. The semanti ..."
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Cited by 23 (3 self)
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We present a declarative language,PP, for the highlevel specification of preferences between possible solutions (or trajectories) of a planning problem. This novel language allows users to elegantly express nontrivial, multidimensional preferences and priorities over such preferences. The semantics ofPP allows the identification of most preferred trajectories for a given goal. We also provide an answer set programming implementation of planning problems with PP preferences.
Complex Preferences for Answer Set Optimization
, 2004
"... preference description language PDL . This language allows us to combine qualitative and quantitative, penalty based preferences in a flexible way. This makes it possible to express complex preferences which are needed in many realistic optimization settings. We show that several preference hand ..."
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Cited by 18 (2 self)
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preference description language PDL . This language allows us to combine qualitative and quantitative, penalty based preferences in a flexible way. This makes it possible to express complex preferences which are needed in many realistic optimization settings. We show that several preference handling methods described in the literature are special cases of our approach. We also demonstrate that PDL expressions can be compiled to logic programs which can be used as tester programs in a generateandimprove method for finding optimal answer sets.
Preference Handling – An Introductory Tutorial
"... We present a tutorial introduction to the area of preference handling – one of the core issues in the design of any system that automates or supports decision making. The main goal of this tutorial is to provide a framework, or perspective, within which current work on preference handling – represen ..."
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Cited by 14 (0 self)
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We present a tutorial introduction to the area of preference handling – one of the core issues in the design of any system that automates or supports decision making. The main goal of this tutorial is to provide a framework, or perspective, within which current work on preference handling – representation, reasoning, and elicitation – can be understood. Our intention is not to provide a technical description of the diverse methods used, but rather, to provide a general perspective on the problem and its varied solutions and to highlight central ideas and techniques.
Inspecting and Preferring Abductive Models
, 2008
"... This work proposes the application of preferences over abductive logic programs as an appealing declarative formalism to model choice situations. In particular, both a priori and a posteriori handling of preferences between abductive extensions of a theory are addressed as complementary and essentia ..."
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Cited by 6 (6 self)
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This work proposes the application of preferences over abductive logic programs as an appealing declarative formalism to model choice situations. In particular, both a priori and a posteriori handling of preferences between abductive extensions of a theory are addressed as complementary and essential mechanisms in a broader framework for abductive reasoning. Furthermore, both of these choice mechanisms are combined with other formalisms for decision making, like economic decision theory, resulting in theories containing the best advantages from both qualitative and quantitative formalisms. Several examples are presented throughout to illustrate the enounced methodologies. These have been tested in our implementation, which we explain in detail.
On preferring and inspecting abductive models
 In Procs. 11th Intl. Symp. Practical Aspects of Declarative Languages (PADL’09), LNCS 5418
, 2009
"... Abstract. This work proposes the application of preferences over abductive logic programs as an appealing declarative formalism to model choice situations. In particular, both a priori and a posteriori handling of preferences between abductive extensions of a theory are addressed as complementary an ..."
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Cited by 5 (5 self)
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Abstract. This work proposes the application of preferences over abductive logic programs as an appealing declarative formalism to model choice situations. In particular, both a priori and a posteriori handling of preferences between abductive extensions of a theory are addressed as complementary and essential mechanisms in a broader framework for abductive reasoning. Furthermore, both of these choice mechanisms are combined with other formalisms for decision making, like economic decision theory, resulting in theories containing the best advantages from both qualitative and quantitative formalisms. Several examples are presented throughout to illustrate the enounced methodologies. These have been tested in our implementation, which we explain in detail. Key words. Abduction, Preferences, Logic Programming, XSBProlog, Smodels 1
Answer Sets: From Constraint Programming Towards Qualitative Optimization
 IN PROCEEDINGS LPNMR04, 34–46
, 2004
"... One of the major reasons for the success of answer set programming in recent years was the shift from a theorem proving to a constraint programming view: problems are represented such that stable models, respectively answer sets, rather than theorems correspond to solutions. This shift in perspe ..."
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Cited by 5 (1 self)
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One of the major reasons for the success of answer set programming in recent years was the shift from a theorem proving to a constraint programming view: problems are represented such that stable models, respectively answer sets, rather than theorems correspond to solutions. This shift in perspective proved extremely fruitful in many areas. We believe that going one step further from a "hard" to a "soft" constraint programming paradigm, or, in other words, to a paradigm of qualitative optimization, will prove equally fruitful. In this paper we try to support this claim by showing that several generic problems in logic based problem solving can be understood as qualitative optimization problems, and that these problems have simple and elegant formulations given adequate optimization constructs in the knowledge representation language.
Pre and post preferences over abductive models
 PROCS. MULTIDISCIPLINARY WORKSHOP ON ADVANCES IN PREFERENCE HANDLING (MPREF’07), 33RD INTL. CONF. ON VERY LARGE DATA BASES (VLDB’07
, 2007
"... This work proposes the application of preferences over abductive logic programs as an appealing declarative formalism to model choice situations. In particular, both a priori and a posteriori handling of preferences between abductive extensions of a theory are addressed as complementary and essentia ..."
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Cited by 4 (3 self)
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This work proposes the application of preferences over abductive logic programs as an appealing declarative formalism to model choice situations. In particular, both a priori and a posteriori handling of preferences between abductive extensions of a theory are addressed as complementary and essential mechanisms in a broader framework for abductive reasoning. Furthermore, both of these choice mechanisms are combined with other formalisms for decision making, like economic decision theory, resulting in theories containing the best advantages from both qualitative and quantitative formalisms. Several examples are presented throughout to illustrate the enounced methodologies.
Hierarchical decision making in multiagent systems using answer set programming
, 2005
"... Abstract. We present a multiagent formalism based on extended answer set programming. The system consists of independent agents connected via a communication channel, where knowledge and beliefs of each agent are represented by a logic program. When presented with an input set of literals from its ..."
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Cited by 4 (0 self)
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Abstract. We present a multiagent formalism based on extended answer set programming. The system consists of independent agents connected via a communication channel, where knowledge and beliefs of each agent are represented by a logic program. When presented with an input set of literals from its predecessor, an agent computes its output as an extended answer set of its program enriched with the input, carefully eliminating contradictions that might occur. It turns out that while individual agents are rather simple, the interaction strategy makes the system quite expressive: essentially a hierarchy of a fixed number of agents n captures the complexity class Σ P n, i.e. the nth level of the polynomial hierarchy. Furthermore, unbounded hierarchies capture the polynomial hierarchy PH. This makes the formalism suitable for modelling complex applications of MAS, for example cooperative diagnosis. Furthermore, such systems can be realized by implementing an appropriate control strategy on top of existing solvers such as DLV and SMODELS. 1
MaxASP: Maximum Satisfiability of Answer Set Programs ⋆
"... Abstract. This paper studies answer set programming (ASP) in the generalized context of soft constraints and optimization criteria. In analogy to the wellknown MaxSAT problem of maximum satisfiability of propositional formulas, we introduce the problems of unweighted and weighted MaxASP. Given a ..."
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Cited by 2 (0 self)
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Abstract. This paper studies answer set programming (ASP) in the generalized context of soft constraints and optimization criteria. In analogy to the wellknown MaxSAT problem of maximum satisfiability of propositional formulas, we introduce the problems of unweighted and weighted MaxASP. Given a normal logic program P, in MaxASP the goal is to find so called optimal MaxASP models, which minimize the total cost of unsatisfied rules in P and are at the same time answer sets for the set of satisfied rules in P. Inference rules for MaxASP are developed, resulting in a complete branchandbound algorithm for finding optimal models for weighted MaxASP instances. Differences between the MaxASP problem and earlier proposed related concepts in the context of ASP are also discussed. Furthermore, translations between MaxASP and MaxSAT are studied. 1