CK-LOG, A Calculus for Knowledge Processing in Logic

: This report introduces the principal concepts in the organization and operation of the logic-based knowledge processing system, called CK-LOG (A Calculus for Knowledge in LOGic). CK-LOG uses the frame-based system MDS (the Meta Description System) for knowledge representation and for modelling world states. It uses an inference engine based on natural Deduction for stating and solving problems. The operation of CK-LOG is discussed here in the context fo OPPLAN-CONSULTANT, an expert consultation system for Naval Operational Planning that is now being designed using the CK-LOG formalism. CK-LOG itself is currently under implementation. This report establishes the descriptive adequacy of CK-LOG to state and represent military planning knowledge needed for operational planning, as well as its problem solving adequacy to use this knowledge automatically to help military commanders design operational plans to achieve given military objectives. The organization of the planning knowledge and the planning processes in OPPLAN-CONSULTANT are directly applicable to the Battle Management Program of the Strategic Computing Initiative. As a knowledge processing system. CK-LOG has several capabilities which are new to the technology of knowledge representation systems: CK-LOG has special facilities to represent and reason about actions and their time dependencies. The theorem-proving system of CK-LOG uses a variant of the calculus of sequents first proposed by Kanger (which itself is a variant of Gentzen's system). The various features of CK-LOG are described in this report.

Knowledge processing is an essential technique for enabling autonomous robots to do the right thing to the right object in the right way. Using knowledge processing the robots can achieve more flexible and general behavior and better performance. While knowledge representation and reasoning has been a well-established research field in artificial intelligence for several decades, little work has been done to design and realize knowledge processing mechanisms for the use in the context of robotic control. In this paper, we report on KNOWROB, a knowledge processing system particularly designed for autonomous personal robots. KNOWROB is a first-order knowledge representation based on description logics that provides specific mechanisms and tools for action-centered representation, for the automated acquisition of grounded concepts through observation and experience, for reasoning about and managing uncertainty, and for fast inference - knowledge processing features that are particularly necessary for autonomous robot control.

Knowledge processing has patterns which can be found in biological neuron activity and artificial neural networks. The work explores whether an underlying structure exists for knowledge which crosses domains. The results show common data processing patterns in biological systems and human-made knowledge-based systems, present examples of human-generated knowledge processing systems, such as artificial neural networks and research topic knowledge networks, and explore change of system patterns over time. The work analyzes nature-based systems, which are animal connectomes, and observes neuron circuitry of knowledge processing based on complexity of the knowledge processing system. The variety of domains and similarity in processing mechanisms raise the question: if it is common in natural and artificial systems to see this pattern-based knowledge processing, how unique is knowledge processing in humans.

The paper presents an approach to the development of a software environment for creation of intelligent systems. This environment is based on an integrated knowledge representation model that combines both classic knowledge representation means and constraint programming methods with agent-based techniques. In contrast to other systems following constraint programming methods, the environment presented here allows one to manipulate objects with imprecise (subdefinite) values of attributes. The process of refining such subdefinite attributes is performed by means of a special data-driven mechanism. Another feature of the environment is the use of an agent-based technique instead of the traditional production rule technique, in order to increase efficiency of the processes of logical inference and data processing. Due to a natural combination of the data-driven and event-driven mechanisms, the environment can be used for the development of efficient intelli-gent systems for various applications.

Through researching the patterns and mechanism of life behavior of some animals, a knowledge processing system with biologic action feature was suggested by this paper, and the autonomic and creative features of the system were described. Following the thought of artificial life, the system was based on the rules and features that come from investigating the intelligent actives and behaviors of some animals from the view of the epistemology and the information theory. By this, the paper try to give the knowledge processing system some capabilities distinguishing from traditional expert systems like self-learning, auto-growing and adaptive. A framework that consist of modules such as auto-fetch module, action controller, refresh module, adaptive human-computer interface, information storage module and so on was assumed. At the same time, the functions of each component of the system were discussed in detail. On the other hand, this paper also attention to the question how to accomplish the system. As a result, a hierarchy structure of the knowledge processing system was put forward, which included function layer, intelligent layer, appetent layer and the basic layer that lies the bottom of the whole structure.

Existing knowledge processing systems, especially expert systems, do not always fit to a company's needs. This reduces the benefits of such a technology, or even completely prevents their usage. Therefore, an architectural guideline is needed to enable software engineers to design and implement custom knowledge processing systems. In this paper a first approach via a pattern language for knowledge processing systems, consisting of five patterns covering the basic components needed, is presented. The patterns were extracted from three different open source expert systems / rule engines. The applicability of the patterns is discussed by applying them on an example custom knowledge processing system project that shows how the pattern language supports the design and implementation.

Knowledge and value: A new perspective on corporate transformation: Solveig Wikstrom and Richard Norman, Routledge (1994), 149 pp., £10.99

Linguistic parameters alone cannot determine the interpretation of natural language utterances. They can only constrain their interpretation and must leave the rest to other knowledge sources and other processes: language understanding is not just a matter of knowing the language, but also to a considerable degree a matter of logical inference and world knowledge. This is no news as far as the interpretation of referential expressions is concerned. Predicate expressions, however, tend to be treated as if they were functional or relational constants that are directly interpreted with respect to a model. In this paper an attempt is made to treat them too as referential. The only real difference is that the referents of predicate expressions are of a different type: concepts rather than first-order objects.

LHP: Logical hypergraph link prediction

Information present in any training set of vectors for machine learning can be interpreted in two different ways, either as whole states or as individual atomic units. In this paper, we show that these alternative information distributions are often inherently incongruent within the training set. When learning with a Boltzmann machine, modifications in the network architecture can select one type of distributional information over the other; favouring the activation of either state exemplar or atomic characteristics. This choice of distributional information is of relevance when considering the representation of knowledge in logic. Traditional logic only utilises preference that is the correlate of whole state exemplar frequency. We propose that knowledge representation derived from atomic characteristic activation frequencies is the correlate of compositional typicality, which currently has limited formal definition or application in logic. Further, we argue by counter-example, that any representation of typicality by ‘most preferred model semantics’ is inadequate. We provide a definition of typicality derived from the probability of characteristic features; based on neural network modelling.

Social robots are used to perform mobile manipulation tasks, such as tidying up and carrying, based on instructions provided by humans. A mobile manipulation planner, which is used to exploit the robot’s functions, requires a better understanding of the feasible actions in real space based on the robot’s subsystem configuration and the object placement in the environment. This study aims to realize a mobile manipulation planner considering the world state, which consists of the robot state (subsystem configuration and their state) required to exploit the robot’s functions. In this paper, this study proposes a novel environmental representation called a world state-dependent action graph (WDAG). The WDAG represents the spatial and temporal order of feasible actions based on the world state by adopting the knowledge representation with scene graphs and a recursive multilayered graph structure. The study also proposes a mobile manipulation planning method using the WDAG. The planner enables the derivation of many effective action sequences to accomplish the given tasks based on an exhaustive understanding of the spatial and temporal connections of actions. The effectiveness of the proposed method is evaluated through practical machine experiments performed. The experimental result demonstrates that the proposed method facilitates the effective utilization of the robot’s functions.

The relevance of the chosen issues is determined by the subject of research – the institution of the welfare state, which plays a crucial role in ensuring the normative order in society and the balance of interests between different social groups. It also guarantees the realization of citizens' political and social rights.The study focuses on the transformation of the welfare state's functions and priorities in social policy, influenced by a rapidly changing internal and external environment. The main methodological foundation of the study is theoretical scientific methods and a systematic approach. Due to the interdisciplinary nature of the research, the authors have drawn on both the results of sociological studies and a significant amount of data from international and domestic socio-economic statistics to address the identified issues. The authors have conducted a comprehensive analysis of the factors that contribute to socio-economic change and how these changes directly affect the functioning of the welfare state. They conclude that, despite differences in each country's stable preferences, external and internal socio-economic conditions influence the social functions of states, institutions, and the mechanisms for implementing these functions. Despite the fact that the principles and functions of the welfare state are implemented through specific measures that take into account the economic capabilities of the state, the peculiarities of state-building, national mentality, and the system of basic values, the idea of state paternalism remains at the heart of each model of the welfare state. This idea reflects the concept of state guardianship over the social sphere. In addition, there is a trend towards convergence among models of the welfare state in the modern world, which manifests itself in a steady trend towards unification of mechanisms for implementing social functions of the state and convergence in the scale of redistribution processes.

The catalogue of the 1993 Venice Biennale kicked off with a prognosis for the 21st century. It was entitled Gestaltwandel. Its author: Ernst Janger, who, as title and text amply demonstrate, is still and stubbornly waiting for his planetarian machine prophecies of the new age of the worker to come true.' Except that what was unambiguously fascist in texts like Totale Mobilmachung [Total Mobilization (1930)] or Der Arbeiter [The Worker (1932)] is now couched in a jumble of mythic images about nature and technology, Titans and Gods, that appeals to a certain kind of contemporary Germanic mindset which thrives on a frenzy of ecological apocalypse and immerses itself in a melancholy rehash of romantic nature philosophy and depraved philosophies of history.2 All of it, of course, in the spirit of posthistoire and the postmodern. Janger has always been more chamaeleon than seismograph of the times. The fact that political and metaphysical mush such as JiAnger's musings about the world-state, the increasing spiritualization of the

The current study aims to adopt a new model for creating innovative OERs. The model, called ‘GHOSHEH’, supports OERs through multiple learner-centered strategies with authentic assessments, and focuses on practice and reflection. The model is internally validated based on international experts’ reviews. Rogers’ process for diffusion of innovations is followed in order to introduce and adopt the GHOSHEH model based on a sample of 117 teachers and experts from different states in the Arab world, including Palestine, Jordan, Saudi Arabia, Oman, Kuwait, UAE, Iraq, and Yemen. Mixed methods research is used: qualitative data are collected from a descriptive case study, and quantitative data are collected from the responses of the participants to a questionnaire about adopting the GHOSHEH model. Results reveal that the model involves four main processes: The first is analysis of content and context. The second is implementing sequenced activities that promote reflection, problem solving, and collaboration. The third is a formative assessment followed by providing continuous feedback. The fourth is peer sharing of the created OERs. Moreover, results show that teachers and experts from different states in the Arab world overwhelmingly adopted the model, and there is evidence of the model’s advantages, simplicity, compatibility, trialability, and observability.

Turbo Expert, a knowledge representation and processing language, is the basic support language for expert system construction. Turbo Expert has been implemented for IBM PC and for El'brus multiprocessor systems.