PREFS on Wednesday, August 16th

Introductory Remarks (08:00‑08:15)
Chair: Tran and Pontelli

08:00‑08:15

Welcome and Introduction

Session 1: Invited Talk (08:15‑09:00)

08:15‑09:00

Haifeng Guo (University of Nebraska at Omaha) Logic Programming with Solution Preferences [ppt] Preference logic programming (PLP) is an extension of logic programming for declaratively specifying problems requiring optimization or comparison and selection among alternative solutions to a query. PLP essentially separates the programming of a problem itself from the criteria specification of its optimal solution. The main challenge to implement a PLP system is how the defined solution preferences take effects automatically on pruning suboptimal solutions and their dependents during the computation. In this paper, we present two different strategies to bridge the programming gap between the specification of preferences and their actual implementation. The first strategy is based on a transformation purely at the Prolog level, which unfortunately can only handle the preferences with total-order relations. The second strategy introduces a new built-in predicate for broader applications. The new predicate serves as the interface between the specification and the actual application of solution criteria. With both strategies, we can easily transform a preference logic program into an executable program, where solution preferences can be propagated into recursion so that selecting an optimal solution to a problem only depends on the optimal solutions to its subproblems.

Session 2 (09:00‑10:30)
Chair: Son Cao Tran

09:00‑09:30	Alessandra Mileo (Universita degli Studi di Milano) Torsten Schaub (University of Potsdam) Extending Ordered Disjunctions for Policy Enforcement: Preliminary report We consider advanced policy description specifications in the context of Answer Set Programming (ASP). Motivated by our application scenario, we further extend an existing policy description language, so that it allows for expressing preferences among sets of objects. This is done by extending the concept of ordered disjunctions to cardinality constraints. We demonstrate that this extension is obtained by combining existing ASP techniques and show how it allows for handling advanced policy description specifications.
09:30‑10:00	Pallavi Tambay (Department of Computer Science & Engg, University at Buffalo) Bharat Jayaraman (State University of New York at Buffalo) Relaxation in Preference Logic Programs We address the computational problems arising from relaxation goals in the paradigm of preference logic programming (PLP). A preference logic program is a logic program with two types of predicates: ordinary predicates and optimization predicates. The latter are defined using a combination of `optimization clauses' and `preference clauses'. Any optimization goal may be subject to relaxation, which is a technique for finding suboptimal solutions to the optimization goal. We explore different forms of relaxation in this paper. Next we introduce the more powerful concept of a relaxation goal, and present different variations of this concept: relaxation with respect to the underlying preference order as well as relaxation with respect to additional constraints on the optimization goal (i.e., `what-if' relaxation). The execution of preference logic programs is based upon SLD search trees extended with a preference structure which is determined from the preference clauses of the program. This model crucially depends upon memo-tables for efficiency. This paper shows an extension of the above model that avoids re-computation during the execution of relaxation goals.
10:00‑10:30	James Delgrande (Simon Fraser University) Torsten Schaub (University of Potsdam) Hans Tompits (Vienna University of Technology) A Preference-Based Framework for Updating Logic Programs: Preliminary Report We present an approach to updating logic programs under the answer-set semantics that builds upon existing work on preferences in logic programming. The approach is simple and generic, making use of two distinct counterbalancing techniques: defaultification and preferences. While defaultification resolves potential conflicts by inducing complementary answer sets, preferences then select among these answer sets, yielding the ones generated by rules that have been added more recently. We obtain a framework for updating logic programs that is also easily implementable by off-the-shelf systems.

Break (10:30‑11:00)

Session 3 (11:00‑12:30)
Chair: Enrico Pontelli

11:00‑11:30	Toshiko Wakaki (Shibaura Institute of Technology) Kazuo Tomita (Shibaura Institute of Technology) Compiling Prioritized Circumscription into General Disjunctive Programs Recently we proposed a method of compiling prioritized circumscription into ASP. However, its encoding has the ``guess and check'' structure, where the candidates are generated by the ``guess'' program and the check is expressed by the inconsistency of the ``check'' program.In this paper, we present another method which compiles prioritized circumscription into a single general disjunctive program (GDP) by means of integration of the guess and check programs. The answer sets of the transformed GDP yield models of a given circumscription by emulating the inconsistency of the ``check'' program using integrity constraints. Moreover, thanks to our integration technique, to evaluate a query with respect to prioritized circumscription is easily established by expressing the inconsistency check in a single GDP. Our experimental results show that the performance of the tool we have implemented using our new method has not only improved remarkably, i.e. reduction of runtime as compared to our previous method, but has also exceeded that of the recently developed software tool, prio_circ2dlp, for prioritized circumscription as far as our experiments are concerned.
11:30‑12:00	Tu Phan (Computer Science Dept., New Mexico State University) Tran Son (NMSU) Enrico Pontelli (New Mexico State University) Planning with Preferences Using Constraint Logic Programming We describe the development of a constraint logic programming based system, called CPP, which is capable of generating most preferred plans with respect to a user's preference and evaluate its performance
12:00‑12:30	Mauricio Osorio (UDLA) Claudia Zepeda (Universidad Tecnologica de la Mixteca) Preferences for General Theories in Answer Sets In this paper we introduce preference rules which allow us to specify preferences as an ordering among the possible solutions of a problem. Our approach allow us to express preferences for general theories. The formalism used to develop our work is Answer Set Programming. Two distinct semantics for preference logic programs are proposed. Finally, some properties that help us to understand these semantics are also presented.