The paper introduces a logical framework for negotiation among dishonest agents. The framework relies on the use of abductive logic programming as a knowledge representation language for agents to deal with incomplete information and preferences. The paper shows how intentionally false or inaccurate information of agents could be encoded in the agents' knowledge bases. Such disinformation can be effectively used in the process of negotiation to have desired outcomes by agents. The negotiation processes are formulated under the answer set semantics of abductive logic programming and enable the exploration of various strategies that agents can employ in their negotiation

This paper studies a computational logic for dishonest reasoning. We introduce logic programs with disinformation to represent and reason with dishonesty. We then consider two different cases of dishonesty: deductive dishonesty and abductive dishonesty. The former misleads another agent to deduce wrong conclusions, while the latter interrupts another agent to abduce correct explanations. In deductive or abductive dishonesty, an agent can perform different types of dishonest reasoning such as lying, bullshitting, and withholding information. We show that these different types of dishonest reasoning are characterized by extended abduction, and address their computational methods using abductive logic programming.

We study the problem of dealing with inconsistency in Description Logic (DL) ontologies. We consider inconsistency-tolerant semantics recently proposed in the literature, called AR-semantics and CAR-semantics, which are based on repairing (i.e., modifying) in a minimal way the extensional knowledge (ABox) while keeping the intensional knowledge (TBox) untouched. We study instance checking and conjunctive query entailment under the above inconsistency-tolerant semantics for a wide spectrum of DLs, ranging from tractable ones (EL) to very expressive ones (SHIQ), showing that reasoning under the above semantics is inherently intractable, even for very simple DLs. To the aim of overcoming such a high computational complexity of reasoning, we study sound approximations of the above semantics. Surprisingly, our computational analysis shows that reasoning under the approximated semantics is intractable even for tractable DLs. Finally, we identify suitable language restrictions of such DLs allowing for tractable reasoning under inconsistency-tolerant semantics.

We consider a generalization of instance retrieval over knowledge bases that provides users with assertions in which descriptions of qualifying objects are given in addition to their identifiers. Notably, this involves a transfer of basic database paradigms involving caching and query rewriting in the context of an assertion retrieval algebra. We present an optimization framework for this algebra, with a focus on finding plans that avoid any need for general knowledge base reasoning at query execution time when sufficient cached results of earlier requests exist.

As a doxastic counterpart to epistemic logic based on S5 we study the modal logic KSD that can be viewed as an approach to modelling a kind of objective and fair belief. We apply KSD to the problem of minimal belief and develop an alterna- tive approach to nonmonotonic modal logic using a weaker concept of expansion. This corresponds to a certain minimal kind of KSD model and yields a new type of nonmonotonic doxastic reasonin

As more and more application areas require higher scalability, the study of fragments of expressive The high computational complexity of the expressive DLs with better computational properties has become an Description Logics (DLs) that underlie the important area of research. OWL standard has motivated the study of their Horn fragments of DLs, which are obtained by restricting Horn fragments, which are usually tractable in data the syntax of a DL in such a way that disjunction is not complexity and can also have lower combined complexity, expressible, were first considered in [Hustadt et al., 2005] particularly for query answering. In this paper as expressive fragments with tractable data complexity (see we provide algorithms for answering conjunctive also [Krötzsch et al., 2007]). It was later identified that they 2-way regular path queries (2CRPQs), a nontrivial can also exhibit lower combined complexity when it comes generalization of plain conjunctive queries, to query answering. Indeed, answering conjunctive queries in the Horn fragments of the DLs SHOIQ and (CQs), a kind of database-inspired queries that have become SROIQ underlying OWL 1 and OWL 2. We show the standard for querying DLs, is in ExpTime for the Horn that the combined complexity of the problem is ExpTime-complete fragment of the prominent SHIQ [Eiter et al., 2008], while it for Horn-SHOIQ and 2ExpTimecomplete is already 2ExpTime-hard for quite restricted (non Horn) fragments for the more expressive Horn-SROIQ, of SHIQ, like ALCI [Lutz, 2008] and SH [Eiter et but is PTime-complete in data complexity for both.

We present a new and compelling approach to the efficient solution of important computational problems that arise in the context of abstract argumentation. Our approach makes known algorithms defined for restricted fragments generally applicable, at a computational cost that scales with the distance from the fragment. Thus, in a certain sense, we gradually augment tractable fragments. Surprisingly, it turns out that some tractable fragments admit such an augmentation and that others do not. More specifically, we show that the problems of credulous and skeptical acceptance are fixed-parameter tractable when parameterized by the distance from the fragment of acyclic argumentation frameworks. Other tractable fragments such as the fragments of symmetrical and bipartite frameworks seem to prohibit an augmentation: the acceptance problems are already intractable for frameworks at distance 1 from the fragments. For our study we use a broad setting and consider several different semantics. For the algorithmic results we utilize recent advances in fixed-parameter tractability.

Quality control is an essential task within ontology development projects especially when the knowledge formalization is partially automatized. In this paper, we propose a reasoning-based, interactive approach to support the revision of formalized knowledge. We state consistency criteria for revision states and introduce the notion of revision closure, based on which the revision of ontologies is partially automatized. Additionally, we propose a notion of axiom impact which is used to determine a beneficial order of axiom evaluation in order to further increase the effectiveness of ontology revision. Finally, we develop the notion of decision spaces, which are structures for calculating and updating the revision closure and axiom impact. The use of decision spaces saves on average 75% of the costly reasoning operations during a revision.

The ability to predict, or at least recognize, the state of the world that an action brings about, is a central feature of autonomous agents. We propose, herein, a formal framework within which we investigate whether this ability can be autonomously learned. The framework makes explicit certain premises that we contend are central in such a learning task: (i) slow sensors may prevent the sensing of an action's direct effects during learning; (ii) predictions need to be made reliably in future and novel situations. We initiate in this work a thorough investigation of the conditions under which learning is or is not feasible. Despite the very strong negative learnability results that we obtain, we also identify interesting special cases where learning is feasible and useful.

Let us explain our motivations for studying the logic of fuzzy belief and common belief. It is not so unusual that one We formalize reasoning about fuzzy belief and believes something to some degree, or the degree of one's fuzzy common belief, especially incomparable beliefs, belief may be neither 0 nor 1. The notion of fuzzy belief is in multi-agent systems by using a logical system appropriate in such a case. Moreover, the notion of fuzzy based on Fitting's many-valued modal logic, common belief can be appropriate even in a case where any where incomparable beliefs mean beliefs whose degrees agent of a group does not have a fuzzy belief. To see this, are not totally ordered. Completeness and consider the following question. Is there anything that all the decidability results for the logic of fuzzy belief people in the world believe? Strictly speaking, there may be and common belief are established while implicitly no such thing as a common belief among all the people in the exploiting the duality-theoretic perspective on Fitting's world. Even if so, there may be something that most of the logic that builds upon the author's previous people in the world believe.