Epistemic logic and explicit knowledge in distributed programming

: The main interest is in investigating several kinds of implications of stochastic programming models and their uses to provide several types of dialogues between formal models and the decision maker himself under risk-taking situations. First, some stochastic programming models which are often discussed in the literature are presented and parametric evaluations using dual evaluators are attempted. Second, we see a close relationship between these models and the mean-standard deviation analysis mainly developed in the context of portfolio selection theory. Third, we explore utility implications of these models in connection with the expected utility maximization principle. Finally, attempts are made to impute the value(s) of key parameters in each of these models and some other utility models from the actual decision made in the mean-standard devication analysis of framework. (Author)

Model checking is a systematic way of checking the absence of errors in a distributed system, i.e., assessing the functional requirements in a distributed system. However, there are certain challenges in this field, e.g., developing true abstract models and on their basis generalizing/guranteeing results, limited capacity of model checking tools and computational resources, identification of all requirements and their accurate specifications, etc. To understand and face such challenges, it is necessary to apply the prominent model checking techniques to different distributed systems designed for different communication models. In this thesis this challenge is accepted and resultantly encountered issues are discussed/addressed. The results reported are sufficient for advocating the need for applying model checking techniques as debugging. Therefore, we report bugs and the propose fixes but for ambiguous algorithms, we reconstruct them. We model check both fixed and reconstructed algorithms. We assess the following protocols: • Accelerated heartbeat protocols, • Consensus protocols in asynchronous distributed systems, • Group membership protocols and • Efficient algorithms to implement failure detectors in partially synchronous systems. We found that the accelerated heartbeat protocols proposed in [M.G. Gouda and T.M. McGuire, Accelerated Heartbeat Protocols, Proc. Of ICDCS’98], violated some natural and essential properties. We proved the results by giving counterexamples and developed the techniques to address the time-triggered events in mCRL2 and investigated the correct time bounds for all the protocols. Regarding consensus problem, we proved the correctness of the proposed algorithms where the failure detectors are unreliable (i.e., failure detectors may make mistakes). These algorithms are proposed in [T. Deepak Chandra and S. Toueg, Unreliable Failure Detectors for Reliable Distributed Systems, J. ACM, 1996 ]. For the group membership protocols proposed in [Y. Amir, D. Dolev, S. Kramer and D. Malki, Membership Algorithms for Multicast Communication Groups, Springer-Verlag, 1992], we found that the original specifications and the text explaining the protocols can be interpreted in different ways and even some natural interpretations contradict each other. Our formalization with respect to different interpretations showed the violation of claimed properties. So to resolve the ambiguities, we reconstructed the protocols and model-checked them. For analyzing the algorithms proposed in [M. Larrea, S. Arevalo and A.Fernndez, Efficient Algorithms to Implement Unreliable Failure Detectors in Partially Synchronous Systems, Proc. of DISC’99 ], we applied symmetry reduction techniques. We found that every algorithm encounters a deadlock if there is a bounded (yet arbitrarily large) buffer in the communication channel between a pair of nodes. We propose fixes for deadlock avoidance and model check the proposed algorithm in UPPAAL, FDR2 and MCRL2. We also present a comparison of these three tools for model checking one of the given four protocols.

Local properties in modal logic

21 Modal logic and philosophy

We introduce KBE, a modal epistemic logic for reasoning about Knowledge, Belief and Estimation, three attitudes involved in an agent's decision-making process. In our logic, Knowledge and Belief are captured by S4.2, a modal logic holding a distinguished position among the epistemic logics investigated in AI and Philosophy. The Estimation operator of KBE is a kind of generalized 'many' or 'most' quantifier, whose origins go back to the work of J. Burgess and A. Herzig, but its model-theoretic incarnation ('weak filters') has been introduced by K. Schlechta and V. Jauregui. We work with complete weak filters ('weak ultrafilters') as we are interested in situations where an estimation can be always reached. The axiomatization of KBE comprises 'bridge' axioms which reflect the intuitive relationship of 'estimation' to 'knowledge' and 'belief', several introspective properties are shown to hold and it comes out that believing i¾? can be equivalently defined in KBE as 'estimating that i¾? is known', an interesting fact and an indication of the intuitive correctness of the introduced estimation operator. The model theory of KBE comprises a class of frames combining relational Kripke frames with Scott-Montague semantics, in which neighborhoods are collections of 'large' sets of possible worlds. Soundness and completeness is mentioned and a tableaux proof procedure is sketched.

Geospatial technology is still facing a lack of “out of the box” distributed processing solutions which are suitable for the amount and heterogeneity of geodata, and particularly for use cases requiring a rapid response. Moreover, most of the current distributed computing frameworks have important limitations hindering the transparent and flexible control of processing (and/or storage) nodes and control of distribution of data chunks. We investigated the design of distributed processing systems and existing solutions related to Geospatial Big Data. This research area is highly dynamic in terms of new developments and the re-use of existing solutions (that is, the re-use of certain modules to implement further specific developments), with new implementations continuously emerging in areas such as disaster management, environmental monitoring and earth observation. The distributed processing of raster data sets is the focus of this paper, as we believe that the problem of raster data partitioning is far from trivial: a number of tiling and stitching requirements need to be addressed to be able to fulfil the needs of efficient image processing beyond pixel level. We attempt to compare the terms Big Data, Geospatial Big Data and the traditional Geospatial Data in order to clarify the typical differences, to compare them in terms of storage and processing backgrounds for different data representations and to categorize the common processing systems from the aspect of distributed raster processing. This clarification is necessary due to the fact that they behave differently on the processing side, and particular processing solutions need to be developed according to their characteristics. Furthermore, we compare parallel and distributed computing, taking into account the fact that these are used improperly in several cases. We also briefly assess the widely-known MapReduce paradigm in the context of geospatial applications. The second half of the article reports on a new processing framework initiative, currently at the concept and early development stages, which aims to be capable of processing raster, vector and point cloud data in a distributed IT ecosystem. The developed system is modular, has no limitations on programming language environment, and can execute scripts written in any development language (e.g. Python, R or C#).

The slogan ‘Evidence of evidence is evidence’ is obscure. It has been applied to connect evidence in one situation to evidence in another. The link may be diachronic or interpersonal. Is present evidence of past or future evidence for p present evidence for p? Is evidence for me of evidence for you for p evidence for me for p? The chapter discusses intra-perspectival evidential links. Is present evidence for me of present evidence for me for p present evidence for me for p? Unless the connection holds between a perspective and itself, it is unlikely to hold between distinct perspectives. Evidence will be understood probabilistically, using formal models from epistemic logic. Bridge principles between first-level and higher-level epistemic conditions often imply versions of controversial principles, such as positive and negative introspection. Formalizations of intra-perspectival principles that evidence of evidence is evidence have similarly implausible connections.

Theory of Mind, the cognitive capacity to attribute internal mental states to oneself and others, is a crucial component of social skills. Its formal study has become important, witness recent research on reasoning and information update by intelligent agents, and some proposals for its formal modelling have put forward settings based on Epistemic Logic (EL). Still, due to intrinsic idealisations, it is questionable whether EL can be used to model the high-order cognition of ‘real’ agents. This manuscript proposes a mental attribution modelling logical framework that is more in-line with findings in cognitive science. We introduce the setting and some of its technical features, and argue why it does justice to empirical observations, using it for modelling well-known False-Belief Tasks.

The study is to show the similarities between J. Fodor's Language of Thought hypothesis and epistemic modal logic. According to the J. Fodor's hypothesis there is the language of thought (also called Mentalese) that is the meta-language in which mental representations of attitudes of organism to propositions expressed in object-language (for example: knowledge, belief, hope, desire, statement) are formulated. These attitudes are called attitudes. In the hypothesis propositional attitudes are thoughts and relations between organism and proposition. Propositional attitudes are of interest for epistemic modal logics. In epistemic logics propositional attitudes are relations considered as modalities, i.e. propositions with modal operators. On certain conditions J. Fodor's Language of Thought hypothesis may be considered as a sort of epistemic modal logic, only it would require certain updating as a formal logical system. The similarities between J. Fodor's Language of Thought and epistemic modal logics give two opportunities. First opportunity is to make special version of epistemic modal logic as an instrument of research for cognitive psychology based on J. Fodor's Language of Thought hypothesis. Second opportunity is to accept the idea of J. Fodor's Language of Thought as an innate language and to attain comprehension that epistemic modal logics are not especially constructed formal languages (formal systems) but innate cognitive programs. It might enable to extrapolate the idea of innate languages onto all formal languages including logical languages and to attempt verifying that idea experimentally within cognitive sciences.

There has been a significant interest in modal logics with intersection, prominent examples including epistemic and doxastic logics with distributed knowledge, propositional dynamic logic with intersection, and description logics with concept intersection. Completeness proofs for such logics tend to be complicated, in particular on model classes such as S5 used, e.g., in standard epistemic logic, mainly due to the undefinability of intersection of modalities in standard modal logic. A standard proof method for the S5 case uses an “unraveling-folding” technique to achieve a treelike model to deal with the problem of undefinability. This method, however, is not easily adapted to other logics, due to its reliance on S5 in a number of steps. In this paper we demonstrate a simpler and more general proof technique by building a treelike canonical model directly, which avoids the complications in the processes of unraveling and folding. We illustrate the technique by showing completeness of the normal modal logics K, D, T, B, S4 and S5 extended with intersection modalities. Furthermore, these treelike canonical models are compatible with Fischer-Ladner-style closures, and we combine the methods to show the completeness of the mentioned logics further extended with transitive closure of union modalities known from PDL or epistemic logic. Some of these completeness results are new.

An active set is a unifying space being able to act as a “bridge” for transferring information, ideas and results between distinct types of uncertainties and different types of applications. An active set is a set of agents who independently deliver true or false values for a given proposition. It is not a simple vector of logic values for different propositions, the results are a vector but the set is not. The difference between an ordinary set and active set is that the ordinary set has passive elements with values of the attributes defined by an external agent, in the active set any element is an agent that internally defines the value of a given attribute for a passive element. So agents in many cases are in a logic conflict and this generates semantic uncertainty on the evaluation. Criteria and agents are the two variables by which we give different logic values to the same attribute or proposition. In modal logic, given a proposition, we can evaluate the proposition only when we know the worlds where the proposition is located. In epistemic logic any world is an agent that knows that the proposition is true or false. The active set is a set of agents as in epistemic logic but the difference with modal logic is that all the agents (worlds) are not separate but are joined in the evaluation of the given proposition. In active set for one agent and one criteria we have one logic value but for many agents and criteria the evaluation is not true or false but is a matrix of true and false. This matrix is not only a logic evaluation as in the modal logic but give us the conflicting structure of the active set evaluation. The agent multi dimensional space to evaluate active set also includes the Hilbert multidimensional space where is possible to simulate quantum logic gate. New logic operation are possible as fuzzy gate operations and more complex operations as conflicting solving, consensus operations, syntactic inconsistency, semantic inconsistency and knowledge integration. In the space of the agents evaluations morphotronic geometric operations are a new frontier to model new types of computers. In this paper we show the connection between classical, fuzzy, evidence theory and active sets.

We give a simple proof of a recently obtained in [12] result on the completeness of modal logics with the modality that corresponds to the intersection of accessibility relations in a Kripke model. In epistemic logic, this is the so-called distributed knowledge operator. We prove completeness for the logics in the modal languages of two types: one has the modalities □1,...,□n for the relations R1,...,Rn that satisfy a unimodal logic L, and the modality □n+1 for the intersection Rn+1=R1 ∩...∩ Rn; the other language has the modalities □i (i ∈ Σ) for the relations Ri that satisfy the logic L, and, for every nonempty subset of indices I ⊆ Σ, the modality □I for the intersection ∩i∈I Ri. While in [12] the completeness is proved only for the logics over K, KD, KT, K4, S4, and S5, here we give a "uniform" construction that enables us to obtain completeness for the logics with intersection over the 15 so-called "traditional" modal logics KΛ, for Λ ⊆ {D, T, B, 4, 5}. The proof method is based on unravelling of a frame and then taking the Horn closure of the resulting frame.

On the succinctness of some modal logics

In multi-agent systems, an agent generally forms her belief based on information from multiple sources, such as messages from other agents or perception of the external environment. While modal epistemic logic has been a standard formalism for reasoning about agent's belief, it lacks the expressive power for tracking information sources. Justification logic (JL) provides the missing expressivity by using justification terms to keep track of the belief formation process. However, because JL does not make a clear distinction between potential and actual evidence, the interpretation of justification formulas in JL turns out to be ambiguous. In this paper, we present a justification-based multi-source reasoning formalism built upon second-order propositional modal logic. Our framework not only inherits the source-tracking advantage of JL but also allows the distinction between the actual observation and simply potential admissibility of evidence.

It is an undeniable fact that software plays an important role in our lives. We use the software to play our music, to check our e-mail, or even to help us drive our car. Thus, the quality of software directly influences the quality of our lives. However, the traditional Software Engineering paradigm is not able to cope with the increasing demands in quantity and quality of produced software. Thus, a new paradigm of Model Driven Software Engineering (MDSE) is quickly gaining ground. MDSE promises to solve some of the problems of traditional Software Engineering (SE) by raising the level of abstraction. Thus, MDSE proposes the use of models and model transformations, instead of textual program files used in traditional SE, as means of producing software. The models are usually graph-based, and are built by using graphical notations – i.e. the models are represented diagrammatically. The advantages of using graphical models over text files are numerous, for example it is usually easier to deduce the relations between different model elements in their diagrammatic form, thus reducing the possibility of defects during the production of the software. Furthermore, formal model transformations can be used to produce different kinds of artifacts from models in all stages of software production. For example, artifacts that can be used as input for model checkers or simulation tools can be produced. This enables the checking or simulation of software products in the early phases of development, which further reduces the probability of defects in the final software product. However, methods and techniques to support MDSE are still not mature enough. In particular methods and techniques for model configuration management (MCM) are still in development, and no generic MCM system exists. In this thesis, I describe my research which was focused on developing methods and techniques to support generic model configuration management. In particular, during my research, I focused on developing methods and techniques for supporting model evolution and model co-evolution. Described methods and techniques are generic and are suitable for a state-based approach to model configuration management. In order to support the model evolution, I developed methods for the representation, calculation, and visualization of state-based model differences. Unlike in previously published research, where these three aspects of model differences are dealt with in separation, in my research all these three aspects are integrated. Thus, the result of model differences calculation algorithm is in the format which is described by my research on model differences representation. The same representation format of model differences is used as a basis of my approach to differences visualization. It is important to notice that the developed representation format for model differences is metamodel independent, and thus is generic, i.e., it can be used to represent differences between all graph-based models. Model co-evolution is a term that describes the problem of adapting models when their metamodels evolve. My solution to this problem has three steps. In the first step a special metamodel MMfMM is introduced. Unlike in traditional approaches, where metamodels are represented as instances of a metametamodel, in my approach the metamodels are represented by models which are instances of an MMfMM. In the second step, since metamodels are represented by models, previously defined methods and techniques for model evolution are reused to represent and calculate the metamodel differences. In the final step I define an algorithm that uses the calculated metamodel differences to adapt models conforming to the evolved metamodel. In order to validate my approaches to model evolution and model co-evolution, I have developed a tool for comparing models and visualizing resulting differences, and a tool for model co-evolution. Moreover, I have developed a method to compare tools for model comparison, and using this method I have conducted a series of experiments in which I compared the tool I developed to an industrial tool called EMFCompare. The results of these experiments are also presented in the thesis. Furthermore, in order to validate my tool and approach to model co-evolution, I have also specified and conducted several experiments. The results of these experiments are also presented in the thesis.