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Yisong Wang

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11 papers
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11

IJCAI Conference 2025 Conference Paper

Witnesses for Answer Sets of Basic Logic Programs

  • Yisong Wang
  • Xianglong Wang
  • Zhongtao Xie
  • Thomas Eiter

Explanation plays an important role in the decisions of both symbolic and neural network-based AI systems. Logic programs under answer set semantics (ASP) have been a typical declarative reasoning and problem-solving paradigm that has extensive applications in various AI domains. In this paper, we consider the issue of explanation for logic programs with abstract constraint atoms (c-atoms) under SPT-answer set semantics. Such c-atoms are general enough to capture complex constructors of logic programs, including aggregates, and the SPT-answer sets exclude circular justifications that other semantics have. We propose a minimal reduct for logic programs with c-atoms that yields a new semantic characterization of SPT-answer sets, and then introduce an extension of resolution for clauses with c-atoms. As we show, every atom in an SPT-answer set enjoys an extended resolution proof from the minimal reduct of its logic program. Finally, we present minimal sufficient subsets of logic programs (witnesses) to structure such an extended resolution proof for an atom in an SPT-answer set. Our results contribute to the justification of answer sets and provide a basis for explainability of ASP-based applications.

ICLR Conference 2024 Conference Paper

HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments

  • Qinhong Zhou
  • Sunli Chen
  • Yisong Wang
  • Haozhe Xu
  • Weihua Du
  • Hongxin Zhang
  • Yilun Du
  • Joshua B. Tenenbaum

Recent advances in high-fidelity virtual environments serve as one of the major driving forces for building intelligent embodied agents to perceive, reason and interact with the physical world. Typically, these environments remain unchanged unless agents interact with them. However, in real-world scenarios, agents might also face dynamically changing environments characterized by unexpected events and need to rapidly take action accordingly. To remedy this gap, we propose a new simulated embodied benchmark, called HAZARD, specifically designed to assess the decision-making abilities of embodied agents in dynamic situations. HAZARD consists of three unexpected disaster scenarios, including fire, flood, and wind, and specifically supports the utilization of large language models (LLMs) to assist common sense reasoning and decision-making. This benchmark enables us to evaluate autonomous agents' decision-making capabilities across various pipelines, including reinforcement learning (RL), rule-based, and search-based methods in dynamically changing environments. As a first step toward addressing this challenge using large language models, we further develop an LLM-based agent and perform an in-depth analysis of its promise and challenge of solving these challenging tasks. HAZARD is available at https://vis-www.cs.umass.edu/hazard/.

KR Conference 2020 Conference Paper

On Sufficient and Necessary Conditions in Bounded CTL: A Forgetting Approach

  • Renyan Feng
  • Erman Acar
  • Stefan Schlobach
  • Yisong Wang
  • Wanwei Liu

Computation Tree Logic (CTL) is one of the central formalisms in formal verification. As a specification language, it is used to express a property that the system at hand is expected to satisfy. From both the verification and the system design points of view, some information content of such property might become irrelevant for the system due to various reasons, e. g. , it might become obsolete by time, or perhaps infeasible due to practical difficulties. Then, the problem arises on how to subtract such piece of information without altering the relevant system behaviour or violating the existing specifications over a given signature. Moreover, in such a scenario, two crucial notions are informative: the strongest necessary condition (SNC) and the weakest sufficient condition (WSC) of a given property. To address such a scenario in a principled way, we introduce a forgetting-based approach in CTL and show that it can be used to compute SNC and WSC of a property under a given model and over a given signature. We study its theoretical properties and also show that our notion of forgetting satisfies existing essential postulates of knowledge forgetting. Furthermore, we analyse the computational complexity of some basic reasoning tasks for the fragment CTLAF in particular.

AAAI Conference 2015 Conference Paper

Knowledge Forgetting in Circumscription: A Preliminary Report

  • Yisong Wang
  • Kewen Wang
  • Zhe Wang
  • Zhiqiang Zhuang

The theory of (variable) forgetting has received significant attention in nonmonotonic reasoning, especially, in answer set programming. However, the problem of establishing a theory of forgetting for some expressive nonmonotonic logics such as McCarthy’s circumscription is rarely explored. In this paper a theory of forgetting for propositional circumscription is proposed, which is not a straightforward adaption of existing approaches. In particular, some properties that are essential for existing proposals do not hold any longer or have to be reformulated. Several useful properties of the new forgetting are proved, which demonstrate suitability of the forgetting for circumscription. A sound and complete algorithm for the forgetting is developed and an analysis of computational complexity is given.

IJCAI Conference 2015 Conference Paper

On Forgetting Postulates in Answer Set Programming

  • Jianmin Ji
  • Jia-Huai You
  • Yisong Wang

Forgetting is an important mechanism for logicbased agent systems. A recent interest has been in the desirable properties of forgetting in answer set programming (ASP) and their impact on the design of forgetting operators. It is known that some subsets of these properties are incompatible, i. e. , they cannot be satisfied at the same time. In this paper, we are interested in the question on the largest set ∆ of pairs (Π, V ), where Π is a logic program and V is a set of atoms, such that a forgetting operator exists that satisfies all the desirable properties for each (Π, V ) in ∆. We answer this question positively by discovering the precise condition under which the knowledge forgetting, a well-established approach to forgetting in ASP, satisfies the property of strong persistence, which leads to a sufficient and necessary condition for a forgetting operator to satisfy all the desirable properties proposed in the literature. We explore computational complexities on checking the condition and present a syntactic characterization which can serve as the basis of computing knowledge forgetting in ASP.

IJCAI Conference 2013 Conference Paper

Forgetting for Answer Set Programs Revisited

  • Yisong Wang
  • Kewen Wang
  • Mingyi Zhang

A new semantic forgetting for answer set programs (ASP), called SM-forgetting, is proposed in the paper. It distinguishes itself from the others in that it preserves not only skeptical and credulous consequences on unforgotten variables, but also strong equivalence – forgetting same variables in strongly equivalent logic programs has strongly equivalent results. The forgetting presents a positive answer to Gabbay, Pearce and Valverde’s open question – if ASP has uniform interpolation property. We also investigate some properties, algorithm and computational complexities for the forgetting. It shows that computing the forgetting result is generally intractable even for Horn logic programs.

AAAI Conference 2012 Conference Paper

A Well-Founded Semantics for Basic Logic Programs with Arbitrary Abstract Constraint Atoms

  • Yisong Wang
  • Fangzhen Lin
  • Mingyi Zhang
  • Jia-Huai You

Logic programs with abstract constraint atoms proposed by Marek and Truszczynski are very general logic programs. They are general enough to capture aggregate logic programs as well as recently proposed description logic programs. In this paper, we propose a wellfounded semantics for basic logic programs with arbitrary abstract constraint atoms, which are sets of rules whose heads have exactly one atom. We show that similar to the well-founded semantics of normal logic programs, it has many desirable properties such as that it can be computed in polynomial time, and is always correct with respect to the answer set semantics. This paves the way for using our well-founded semantics to simplify these logic programs. We also show how our semantics can be applied to aggregate logic programs and description logic programs, and compare it to the wellfounded semantics already proposed for these logic programs.

KR Conference 2012 Short Paper

Forgetting in Logic Programs under Strong Equivalence

  • Yisong Wang
  • Yan Zhang
  • Yi Zhou
  • Mingyi Zhang

Wang (2008) then proposed a semantic forgetting for consistent disjunctive logic programs, which preserves equivalence but not strong equivalence. They specifically indicated the importance of preserving strong equivalence in logic programming forgetting and raised this issue as a future work. Wong (2009) proposed two forgetting operators for disjunctive logic programs. Although Wong’s forgetting indeed preserves strong equivalence, it may lose the intuition of weakening under various circumstances (see Related Work for details). In addition to preserving strong equivalence, expressibility is another desired criterion for logic programming forgetting. Ideally we would expect that the result of forgetting some atoms from a logic program is still expressible by a logic program. Finally, we believe that as a way of weakening, forgetting in logic programs should obey some common intuitions shared by forgetting in classical logics. For instance, forgetting something from a logic program should lead to a weaker program in certain sense. On the other hand, such weakening should only be associated to the relevant information that has been forgotten. For this purpose, Zhang and Zhou (2009) proposed four forgetting postulates to formalize these common intuitions and showed that forgetting in classical propositional logic and modal logic S5 can be precisely captured by these postulates. Interestingly, none of previous forgetting notions in logic programs actually satisfies Zhang-Zhou’s postulates. In summary, we consider the following criteria that a forgetting notion in logic program should meet: • Expressibility. The result of forgetting in an arbitrary logic program should also be expressible via an arbitrary logic program; • Preserving strong equivalence. Two strongly equivalent programs should remain strongly equivalence after forgetting the same set of atoms; • Satisfying common intuitions of forgetting. Preferably, forgetting in logic programs should be semantically characterized by Zhang-Zhou’s four forgetting postulates. In this paper we present a comprehensive study on forgetting in the context of arbitrary logic programs (propositional theories) under answer set semantics. In our approach, a program Π is viewed as a theory of the logic of here-andthere (or simply called HT logic), then forgetting a set V of In this paper, we propose a semantic forgetting for arbitrary logic programs (or propositional theories) under answer set semantics, called HT-forgetting. The HTforgetting preserves strong equivalence in the sense that strongly equivalent logic programs will remain strongly equivalent after forgetting the same set of atoms. The result of an HT-forgetting is always expressible by a logic program, and in particular, the result of an HT-forgetting in a Horn program is expressible in a Horn program; and a representation theorem shows that HT-forgetting can be precisely characterized by Zhang-Zhou’s four forgetting postulates under the logic of here-and-there. We also reveal underlying connections between HTforgetting and classical forgetting, and provide complexity results for decision problems.

TCS Journal 2012 Journal Article

The loop formula based semantics of description logic programs

  • Yisong Wang
  • Jia-Huai You
  • Li Yan Yuan
  • Yi-Dong Shen
  • Mingyi Zhang

Description logic programs (dl-programs) proposed by Eiter et al. constitute an elegant yet powerful formalism for the integration of answer set programming with description logics, for the Semantic Web. In this paper, we generalize the notions of completion and loop formulas of logic programs to description logic programs and show that the answer sets of a dl-program can be precisely captured by the models of its completion and loop formulas. Furthermore, we propose a new, alternative semantics for dl-programs, called the canonical answer set semantics, which is defined by the models of completion that satisfy what are called canonical loop formulas. A desirable property of canonical answer sets is that they are free of circular justifications. Some properties of canonical answer sets are also explored and we compare the canonical answer set semantics with the FLP-semantics and the answer set semantics by translating dl-programs into logic programs with abstract constraints. We present a clear picture on the relationship among these semantics variations for dl-programs.

KR Conference 2008 Conference Paper

Answer Set Programming with Functions

  • Fangzhen Lin
  • Yisong Wang

To compute a function such as a mapping from vertices to colors in the graph coloring problem, current practice in Answer Set Programming is to represent the function as a relation. Among other things, this often makes the resulting program unnecessarily large when instantiated on a large domain. The extra constraints needed to enforce the relation as a function also make the logic program less transparent. In this paper, we consider adding functions directly to normal logic programs. We show that the answer set semantics can be generalized to these programs straightforwardly. We also show that the notions of loops and loop formulas can be extended, and that through program completion and loop formulas, a normal logic program with functions can be transformed to a Constraint Satisfaction problem.

KR Conference 2006 Conference Paper

First-Order Loop Formulas for Normal Logic Programs

  • Fangzhen Lin
  • Yin Chen
  • Yisong Wang
  • Mingyi Zhang

In this paper we extend Lin and Zhao's notions of loops and loop formulas to normal logic programs that may contain variables. Under our definition, a loop formula of such a logic program is a first-order sentence. We show that together with Clark's completion, our notion of first-order loop formulas captures the answer set semantics on the instantiation-basis: for any finite set F of ground facts about the extensional relations of a program P, the answer sets of the ground program obtained by instantiating P using F are exactly the models of the propositional theory obtained by instantiating using F the first order theory consisting of the loop formulas of P and Clark's completion of the union of P and F. We also prove a theorem about how to check whether a normal logic program with variables has only a finite number of non-equivalent first-order loops.

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