this paper, we present a solution to the problem how a team of robotic agents can come up with a hypothesis of what might globally be wrong with the environment in similar situations. Hypotheses should entail the currently observed behavior and provide some kind of "forecast" for those areas that no other member of the team visited so far. As time proceeds the hypothesis will be refined to match the actual situation more closely. With a hypothesis about the condition of the environment, single robots can try to avoid areas that potentially contain obstacles, take the shortest way out of these areas, or instead enter these areas to (dis-)prove the hypothesis dependent on the strategy of the team

Recently, considerable interest and research e#ort has been given to the problem of finding a suitable extension of the logic programming paradigm beyond the class of normal logic programs. In order to demonstrate that a class of programs can be justifiably called an extension of logic programs one should be able to argue that: . the proposed syntax of such programs resembles the syntax of logic programs but it applies to a significantly broader class of programs; . the proposed semantics of such programs constitutes an intuitively natural extension of the semantics of normal logic programs; . there exists a reasonably simple procedural mechanism allowing, at least in principle, to compute the semantics; . the proposed class of programs and their semantics is a special case of a more general non-monotonic formalism which clearly links it to other well-established non-monotonic formalisms. In this paper we propose a specific class of extended logic programs which will be (modestly) called super logic programs or just super-programs. We will argue that the class of super-programs satisfies all of the above conditions, and, in addition, is su#ciently flexible to allow various application-dependent extensions and modifications. We also provide a brief description of a Prolog implementation of a query-answering interpreter for the class of super-programs which is available via FTP and WWW. Keywords: Non-Monotonic Reasoning, Logics of Knowledge and Beliefs, Semantics of Logic Programs and Deductive Databases. # An extended abstract of this paper appeared in the Proceedings of the Fifth International Conference on Principles of Knowledge Representation and Reasoning (KR'96), Boston, Massachusetts, 1996, pp. 529--541. + Partially supported by the National Science Fou...

. Database and Artificial Intelligence applications are briefly discussed and it is argued that they need deduction methods that are not only refutation complete but also complete for finite satisfiability. A novel deduction method is introduced for such applications. Instead of relying on Skolemization, as most refutation methods do, the proposed method processes existential quantifiers in a special manner which makes it complete not only for refutation, but also for finite satisfiability. A main contribution of this paper is the proof of these results. Keywords: Artificial Intelligence, Expert Systems, Databases, Automated Reasoning, Finite Satisfiability. 1 Introduction For many applications of automated reasoning, the tableaux methods [32, 16, 34, 18] have the following advantages: They not only detect unsatisfiability but also generate models; they are close to common sense reasoning, hence easy to enhance with an explanation tool; and they are quite easy to adapt to the special...

In this paper, we argue that the resolution of anaphoric expressions in an utterance is essentially an abductive task following [HSAM93] who use a weighted abduction scheme on horn clauses to deal with reference. We give a semantic representation for utterances containing anaphora that enables us to compute possible antecedents by abductive inference. We extend the disjunctive model construction procedure of hyper tableaux [BFN96, Kuh97] with a clause transformation turning the abductive task into a model generation problem and show the completeness of this transformation with respect to the computation of abuctive explanations. This abductive inference is applied to the resolution of anaphoric expressions in our general model constructing framework for incremental discourse representation [Kuh99] which we argue to be useful for computing information updates from natural language utterances [Vel96].

The stable model semantics of disjunctive logic programs is based on classical models which are minimal with respect to subset inclusion. As a consequence, every atom appearing in a disjunctive program is false by default. This is sometimes undesirable from the knowledge representation point of view and a more refined control of minimization is called for. Such features are already present in Lifschitz's parallel circumscription where certain atoms are allowed to vary or to have fixed values while all other atoms are minimized. In this paper, it is formally shown that the expressive power of minimal models is properly increased in the presence of varying atoms. In spite of this, we show how parallel circumscription can be embedded into disjunctive logic programming in a relatively systematic fashion using a linear and faithful, but non-modular translation. This enables the conscious use of varying atoms in disjunctive logic programs — leading to more elegant and concise problem representations in various domains.

In this paper, we show how techniques from disjunctive logic programming and classical first-order theorem proving can be used for efficient (deductive) database updates. The key idea is to tranform the given database together with the update request into a disjunctive logic program and apply disjunctive techniques (such as minimal model reasoning) to solve the original update problem. We present two variants of our algorithm both of which are of polynomial space complexity. One variant, which is based on offline preprocessing, is of polynomial time complexity. We also show that both variants are rational in the sense that they satisfy certain rationality postulates stemming from philosophical works on belief dynamics.

this paper, we show how techniques from first-order theorem proving can be used for

In this paper we define a new clausal class, called BU, which can be decided by hyperresolution with splitting. We also consider the model generation problem for BU and show that hyperresolution plus splitting can also be used as a Herbrand model generation procedure for BU and, furthermore, that the addition of a local minimality test allows us to generate only minimal Herbrand models for clause sets in BU. In addition, we investigate the relationship of BU to other solvable classes.

. We combine techniques originally developed for refutational first-order theorem proving within the clause tree framework with techniques for minimal model computation developed within the hyper tableau framework. This combination generalizes well-known tableaux techniques like complement splitting and folding-up/down. We argue that this combination allows for efficiency improvements over previous, related methods. It is motivated by application to diagnosis tasks; in particular the problem of avoiding redundancies in the diagnoses of electrical circuits with reconvergent fanouts is addressed by the new technique. In the paper we develop as our main contribution in a more general way a sound and complete calculus for propositional circumscriptive reasoning in the presence of minimized and varying predicates. 1 Introduction Recently clause trees [6], a data structure and calculus for automated theorem proving, introduced a general method to close branches based on so-calle...

This paper describes two hyperresolution-based decision procedures for a subfragment of the guarded fragment. The rst procedure is a polynomial space decision procedure which eectively corresponds to polynomial space tableaux-based algorithms without blocking. The second procedure is a minimal model generation procedure which constructs all and only minimal Herbrand models for guarded formulae. This procedure is based on hyperresolution, complement splitting and a model constraint propagation rule. Both procedures have concrete application domains and are relevant for all multi-modal and description logics that can be embedded into the guarded fragment.