Vivid: A framework for heterogeneous problem solving

We introduce Vivid, a domain-independent framework for mechanized heterogeneous reasoning that combines diagrammatic and symbolic representation and inference. The framework is presented in the form of a family of denotational proof languages (DPLs). We present novel formal structures, called named system states, that are specifically designed for modeling potentially underdetermined diagrams. These structures allow us to deal with incomplete information, a pervasive feature of heterogeneous problem solving. We introduce a notion of attribute interpretations that enables us to interpret first-order relational signatures into named system states, and develop a formal semantic framework based on 3-valued logic. We extend the assumption-base semantics of DPLs to accommodate diagrammatic reasoning by introducing general inference mechanisms for the valid extraction of information from diagrams, and for the incorporation of sentential information into diagrams. A rigorous big-step operational semantics is given, on the basis of which we prove that the framework is sound. We present examples of particular instances of Vivid in order to solve a series of problems, and discuss related work.     

多值逻辑系统W_n中α-三I问题的形式解

在多值逻辑系统Wn中提出了琢-三I问题。通过在F(S)中引入一个偏序,讨论了琢-GMP和多重琢-GMP问题的形式化推理问题,得到了琢-FMP问题的形式化三I解,从而在多值逻辑系统Wn中建立了琢-三I问题的形式化推理机制。     

On the logic of preference and judgment aggregation

Agents that must reach agreements with other agents need to reason about how their preferences, judgments, and beliefs might be aggregated with those of others by the social choice mechanisms that govern their interactions. The emerging field of judgment aggregation studies aggregation from a logical perspective, and considers how multiple sets of logical formulae can be aggregated to a single consistent set. As a special case, judgment aggregation can be seen to subsume classical preference aggregation. We present a modal logic that is intended to support reasoning about judgment aggregation scenarios (and hence, as a special case, about preference aggregation): the logical language is interpreted directly in judgment aggregation rules. We present a sound and complete axiomatisation. We show that the logic can express aggregation rules such as majority voting; rule properties such as independence; and results such as the discursive paradox, Arrow’s theorem and Condorcet’s paradox—which are derivable as formal theorems of the logic. The logic is parameterised in such a way that it can be used as a general framework for comparing the logical properties of different types of aggregation—including classical preference aggregation. As a case study we present a logical study of, including a formal proof of, the neutrality lemma, the main ingredient in a well-known proof of Arrow’s theorem.     

The dynamics of default reasoning

In this paper we study default reasoning from a dynamic, agent-oriented, semantics-based point of view. In a formal framework used to specify and to reason about rational agents, we introduce actions that model the (attempted) jumping to conclusions that is a fundamental part of reasoning by default. Application of such an action consists of three parts. First it is checked whether the formula that the agent tries to jump to is a default, thereafter it is checked whether the default formula can consistently be incorporated by the agent, and if this is the case the formula is included in the agent's beliefs. As for all actions in our framework, we define the ability and opportunity of agents to apply these actions, and the states of affairs following application. To formalise formulae being defaults, we introduce the modality of common possibility. This modality is related to, but not reducible to, the notions of common knowledge and ‘everybody knows’-knowledge. To model the qualitative difference that exists between hard, factual knowledge and beliefs derived by default, we employ different modalities to represent these concepts, thus combining knowledge, beliefs, and defaults in one framework. Based on the concepts used to model the default reasoning of agents, we look into the dynamics of the supernormal fragment of default logic. We show in particular that by sequences of jumps to conclusions agents can end up with extensions in the sense of default logic of their belief.     

Formal Reasoning About Lazy-STM Programs

Transactional memory (TM) is an easy-using parallel programming model that avoids common problems associated with conventional locking techniques. Several researchers have proposed a large amount of alternative hardware and software TM implementations. However, few ones focus on formal reasoning about these TM programs. In this paper, we propose a framework at assembly level for reasoning about lazy software transactional memory (STM) programs. First, we give a software TM implementation based on lightweight locks. These locks are also one part of the shared memory. Then we define the semantics of the model operationally, and the lightweight locks in transaction are non-blocking, avoiding deadlocks among transactions. Finally we design a logic — a combination of permission accounting in separation logic and concurrent separation logic — to verify various properties of concurrent programs based on this machine model. The whole framework is formalized using a proof-carrying-code (PCC) framework.     

Formal semantics of meta‐level architectures: Dynamic control of reasoning

Meta‐level architectures for dynamic control of reasoning processes are quite powerful. In the literature, many applications in reasoning systems modeling complex tasks are described, usually in a procedural manner. In this article we present a semantic framework based on temporal partial logic to describe the dynamics of reasoning behavior. Using these models, the semantics of the behavior of the whole (meta‐level) reasoning system can be described by a set of (intended) temporal models. © 2002 Wiley Periodicals, Inc.     

Aligning Logical and Psychological Perspectives on Diagrammatic Reasoning

We advance a theoretical framework which combines recent insights of research in logic, psychology, and formal semantics, on the nature of diagrammatic representation and reasoning. In particular, we wish to explain the varied efficacy of reasoning and representing with diagrams. In general we consider diagrammatic representations to be restricted in expressive power, and we wish to explain efficacy of reasoning with diagrams via the semantical and computational properties of such restricted `languages'. Connecting these foundational insights (from semantics and complexity theory) to the psychology of reasoning with diagrams requires us to develop the notion of the availability (to an agent) of constraints operating within representation systems, as a consequence of their direct semanticinterpretation. Thus we offer a number of fundamentaldefinitions as well as a research programme which alignscurrent efforts in the logical and psychological analysis ofdiagrammatic representation systems.     

Signed Systems for Paraconsistent Reasoning

We present a novel approach to paraconsistent reasoning, that is, to reasoning from inconsistent information. The basic idea is the following. We transform an inconsistent theory into a consistent one by renaming all literals occurring in the theory. Then, we restore some of the original contents of the theory by introducing progressively formal equivalences linking the original literals to their renamings. This is done as long as consistency is preserved. The restoration of the original contents of the theory is done by appeal to default logic. The overall approach provides us with a family of paraconsistent consequence relations.Our approach is semantical because it works at the level of the propositions; it deals with the semantical link between a proposition and its negation. The approach is therefore independent of the combination of the connectives that are actually applied to the propositions in order to form entire formulas.     

On the interaction between knowledge and social commitments in multi-agent systems

Both knowledge and social commitments have received considerable attention in Multi-Agent Systems (MASs), specially for multi-agent communication. Plenty of work has been carried out to define their semantics. However, the relationship between social commitments and knowledge has not been investigated yet. In this paper, we aim to explore such a relationship from the semantics and model checking perspectives with respect to CTLK logic (an extension of CTL logic with modality for reasoning about knowledge) and CTLC logic (an extension of CTL with modalities for reasoning about commitments and their fulfillments). To analyze this logical relationship, we simply combine the two logics in one new logic named CTLKC. The purpose of such a combination is not to advocate a new logic, but only to express and figure out some reasoning postulates merging both knowledge and commitments as they are currently defined in the literature. By so doing, we identify some paradoxes in the new logic showing that simply combining current versions of commitment and knowledge logics results in a logical language that violates some fundamental intuitions. Consequently, we propose CTLKC⁺, a new logic that fixes the identified paradoxes and allows us to reason about social commitments and knowledge simultaneously in a consistent manner. Furthermore, we address the problem of model checking CTLKC⁺ by reducing it to the problem of model checking GCTL^?, a generalized version of CTL^? with action formulae. By doing so, we directly benefit from CWB-NC, the model checker of GCTL^?. Using this reduction, we also prove that the computational complexity of model checking CTLKC⁺ is still PSPACE-complete for concurrent programs as the complexity of model checking CTLK and CTLC separately.     

Understanding and measuring formal communication quality for technology implementation: A test during the anticipation stage

Successfully introducing new technologies to employees remains a critical and challenging task for managers. Practitioner and academic research points to the crucial role of formal communication in the success of technology implementation. We developed a scale for measuring formal communication quality and assessed its influence using three samples of working professionals who were anticipating new technologies at work. Informed by the coping model of user adaptation, we examined the direct and indirect effects of formal communication quality during the anticipation stage of a technology implementation project on employees’ cognitions, emotions and intention to connect with colleagues in order to prepare themselves for the new technologies. The results validate our conceptualization of formal communication as a second-order formative construct with information quality in four content areas (i.e., what, how, why and when) as the first-order dimensions. Our findings affirm the role of formal communication as a managerial influence mechanism that positively affects an employee’s preliminary evaluation of a new IT during the anticipation stage. The evaluation of the new IT triggered emotions, and the emotions in turn motivated employees to seek opinions and camaraderie from others as a means of adapting to the new IT. Our post hoc analyses illustrate the dynamic nature of the relationship among formal communication quality, beliefs, emotions and coping intentions as the implementation unfolds. Our work contributes to the literature by improving the operationalization of formal communication quality, expanding the current understanding of seeking social support and revealing new insight about the temporal dynamics of the relationships in the nomological network during the anticipation stage. The validated scale of formal communication can be a useful tool for managers who wish to evaluate the effectiveness of their communication and to assess its impact on employees’ adaptation.     

Conditionals,Counterfactuals, and Rational Reasoning: An Experimental Study on Basic Principles

We present a unified approach for investigating rational reasoning about basic argument forms involving indicative conditionals, counterfactuals, and basic quantified statements within coherence-based probability logic. After introducing the rationality framework, we present an interactive view on the relation between normative and empirical work. Then, we report a new experiment which shows that people interpret indicative conditionals and counterfactuals by coherent conditional probability assertions and negate conditionals by negating their consequents. The data support the conditional probability interpretation of conditionals and the narrow-scope reading of the negation of conditionals. Finally, we argue that coherent conditional probabilities are important for probabilistic analyses of conditionals, nonmonotonic reasoning, quantified statements, and paradoxes.     

Assessment of subjective influence and trust with an online social network game

The deduction of influence and trust between two individuals only from objective data in online social networks (OSNs) is a rather vague approach. Subjective assessments via surveys produce better results, but are harder to conduct considering the vast amount of friendships of OSN users. This work presents a framework for personalized surveys on relationships in OSNs, which follows a gamification approach. A Facebook game was developed, which was used to subjectively assess social influence and interpersonal trust based on models from psychology. The results show that it is possible to obtain subjective opinions and (limited) objective data about relationships with an OSN game. Also an implicit assessment of influence and trust with subcategory questions is feasible in this case.     

Know means no: Incorporating knowledge into discrete-event controlsystems

Modal logic is introduced into the modeling of discrete-event systems. Analysis within this framework includes formal reasoning about what supervisors know or do not know about a given system. This model can be used to develop control strategies that solve decentralized discrete-event control problems. When a problem cannot be solved using fully decentralized supervisors, reasoning about knowledge may provide guidelines for incorporating communication and pooled information into the model     

A Computational Framework for Practical Social Reasoning

This article describes a framework for practical social reasoning designed to be used for analysis, specification, and implementation of the social layer of agent reasoning in multiagent systems. Our framework, called the expectation strategy behavior (ESB) framework, is based on (i) using sets of update rules for social beliefs tied to observations (so‐called expectations), (ii) bounding the amount of reasoning to be performed over these rules by defining a reasoning strategy, and (iii) influencing the agent's decision‐making logic by means of behaviors conditioned on the truth status of current and future social beliefs. We introduce the foundations of ESB conceptually and present a formal framework and an actual implementation of a reasoning engine, which is specifically combined with a general (belief–desire–intention‐based) practical reasoning programming system. We illustrate the generality of ESB through select case studies, which show that it is able to represent and implement different typical styles of social reasoning. The broad coverage of existing social reasoning methods, the modularity that derives from its declarative nature, and its focus on practical implementation make ESB a useful tool for building advanced socially reasoning agents.     

Integration of a security type system into a program logic

Type systems and program logics are often thought to be at opposing ends of the spectrum of formal software analyses. In this paper we show that a flow-sensitive type system ensuring non-interference in a simple while-language can be expressed through specialised rules of a program logic. In our framework, the structure of non-interference proofs resembles the corresponding derivations in a state-of-the-art security type system, meaning that the algorithmic version of the type system can be used as a proof procedure for the logic. We argue that this is important for obtaining uniform proof certificates in a proof-carrying code framework. We discuss in which cases the interleaving of approximative and precise reasoning allows us to deal with delimited information release. Finally, we present ideas on how our results can be extended to encompass features of realistic programming languages such as Java.     

Hybrid knowledge bases

Deductive databases that interact with, and are accessed by, reasoning agents in the real world (such as logic controllers in automated manufacturing, weapons guidance systems, aircraft landing systems, land-vehicle maneuvering systems, and air-traffic control systems) must have the ability to deal with multiple modes of reasoning. Specifically, the types of reasoning we are concerned with include, among others, reasoning about time, reasoning about quantitative relationships that may be expressed in the form of differential equations or optimization problems, and reasoning about numeric modes of uncertainty about the domain which the database seeks to describe. Such databases may need to handle diverse forms of data structures, and frequently they may require use of the assumption-based nonmonotonic representation of knowledge. A hybrid knowledge base is a theoretical framework capturing all the above modes of reasoning. The theory tightly unifies the constraint logic programming scheme of Jaffar and Lassez (1987), the generalized annotated logic programming theory of Kifer and Subrahmanian (1989), and the stable model semantics of Gelfond and Lifschitz (1988). New techniques are introduced which extend both the work on annotated logic programming and the stable model semantics     

Computing change and specificity with equational logic programs

Recent deductive approaches to reasoning about action and chance allow us to model objects and methods in a deductive framework. In these approaches, inheritance of methods comes for free, whereas overriding of methods is unsupported. In this paper, we present an equational logic framework for objects, methods, inheritance and overriding of methods. Overriding is achieved via the concept of specificity, which states that more specific methods are preferred to less specific ones. Specificity is computed with the help of negation as failure. We specify equational logic programs and show that their completed versions behave as intended. Furthermore, we prove that SLDENF-resolution is complete if the equational theory is finitary, the completed programs are consistent and no derivation flounders or is infinite. Moreover, we give syntactic conditions which guarantee that no derivation flounders or is infinite. Finally, we discuss how the approach can be extended to reasoning about the past in the context of incompletely specified objects or situations. It will turn out that constructive negation is needed to solve these problems.     

GenCLOn: An ontology for city logistics

City logistics is a discipline specialized to cope with the sustainability problems encountered in urban freight transport. A key characteristic of it is the heterogeneity of the stakeholders involved. Besides the traditional logistics actors such as shippers, carriers and receivers that share consistent interests (i.e. price and quality), city logistics highly respect the interests of public administrators and citizens that care more about the social welfare. To reach an optimal balance between private and public benefit, it is necessary to understand and in turn forecast the behavior pattern of different groups. In recent years, agent-based modeling has been practiced as an unconventional tool to fulfill this task for its strong capability on capturing the dynamic behavior of individual stakeholders and their interconnections. Referring to other domains (e.g. energy system) where the application of agent-based modeling is relatively mature, a following urgency is to achieve interoperability and in turn reusability between models via introducing formal ontology as a shared template with which developers can standardize their models. This paper introduces an initiative of developing an ontology that formalizes the domain knowledge of city logistics.     

Graph theoretical structures in logic programs and default theories

In this paper we present a graph representation of logic programs and default theories. We show that many of the semantics proposed for logic programs with negation can be expressed in terms of notions emerging from graph theory, establishing in this way a link between the fields. Namely the stable models, the partial stable models, and the well-founded semantics correspond respectively to the kernels, semikernels and the initial acyclic part of an associated graph. This link allows us to consider both theoretical (existence, uniqueness) and computational problems (tractability, algorithms, approximations) from a more abstract and rather combinatorial point of view. It also provides a clear and intuitive understanding about how conflicts between rules are resolved within the different semantics. Furthermore, we extend the basic framework developed for logic programs to the case of Default Logic by introducing the notions of partial, deterministic and well-founded extensions for default theories. These semantics capture different ways of reasoning with a default theory.