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Intellectics and Computational Logic
`Intellectics' seeks to understand the functions, structure and operation of the human intellect and to test artificial systems to see the extent to which they can substitute or complement such functions. The word itself was introduced in the early 1980s by Wolfgang Bibel to describe the united fields of artificial intelligence and cognitive science. The book collects papers by distinguished researchers, colleagues and former students of Bibel's, all of whom have worked together with him, and who present their work to him here to mark his 60th birthday. The papers discuss significant issues in intellectics and computational logic, ranging across automated deduction, logic programming, the logic-based approach to intellectics, cognitive robotics, knowledge representation and reasoning. Each paper contains new, previously unpublished, reviewed results. The collection is a state of the art account of the current capabilities and limitations of a computational-logic-based approach to intellectics. Readership: Researchers who are convinced that the intelligent behaviour of machines should be based on a rigid formal treatment of knowledge representation and reasoning.
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Deep Learning with Relational Logic Representations
Deep learning has been used with great success in a number of diverse applications, ranging from image processing to game playing, and the fast progress of this learning paradigm has even been seen as paving the way towards general artificial intelligence. However, the current deep learning models are still principally limited in many ways. This book, ‘Deep Learning with Relational Logic Representations’, addresses the limited expressiveness of the common tensor-based learning representation used in standard deep learning, by generalizing it to relational representations based in mathematical logic. This is the natural formalism for the relational data omnipresent in the interlinked stru...
Foundations of Equational Logic Programming
Equations play a vital role in many fields of mathematics, computer science, and artificial intelligence. Therefore, many proposals have been made to integrate equational, functional, and logic programming. This book presents the foundations of equational logic programming. After generalizing logic programming by augmenting programs with a conditional equational theory, the author defines a unifying framework for logic programming, equation solving, universal unification, and term rewriting. Within this framework many known results are developed. In particular, a presentation of the least model and the fixpoint semantics of equational logic programs is followed by a rigorous proof of the soundness and the strong completeness of various proof techniques: SLDE-resolution, where a universal unification procedure replaces the traditional unification algorithm; linear paramodulation and special forms of it such as rewriting and narrowing; complete sets of transformations for conditional equational theories; and lazy resolution combined with any complete set of inference rules for conditional equational theories.
Computational Logic — CL 2000
These are the proceedings of the First International Conference on Compu- tional Logic (CL 2000) which was held at Imperial College in London from 24th to 28th July, 2000. The theme of the conference covered all aspects of the theory, implementation, and application of computational logic, where computational logic is to be understood broadly as the use of logic in computer science. The conference was collocated with the following events: { 6th International Conference on Rules and Objects in Databases (DOOD 2000) { 10th International Workshop on Logic-based Program Synthesis and Tra- formation (LOPSTR 2000) { 10th International Conference on Inductive Logic Programming (ILP 2000). CL 2000 c...
Challenges for Action Theories
A logic-based approach to the design of computing systems would, undoubtedly, offer many advantages over the imperative paradigm most commonly applied so far for programming and hardware design and, consequently, logic, again and again, has been heralded as the basis for the next generation of computer systems. While logic and formal methods are indeed gaining ground in many areas of computer science and artificial intelligence the expected revolution has not yet happened. In this book the author offers a convincing solution to the ramification problem and qualification problem associated with the frame problem and thus contributes to a satisfactory solution of the core problem and related challenges. Thielscher bases his approach on the fluent calculus, a first-order Prolog-like formalism allowing for the description of actions and change.
Modeling and Using Context
This book constitutes the proceedings of the 10th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT 2017, held in Paris, France, in June 2017. The 26 full papers and 15 short papers presented were carefully reviewed and selected from 88 submissions. The papers feature research in a wide range of disciplines related to issues of context and contextual knowledge and discuss commonalities across and differences between the disciplines' approaches to the study of context. They are organized in the following topical sections: context in representation; context modeling of human activities; context in communication; context awareness; and various specific topics.
KI 2015: Advances in Artificial Intelligence
This book constitutes the refereed proceedings of the 38th Annual German Conference on Artificial Intelligence, KI 2015, held in Dresden, Germany, in September 2015. The 15 revised full technical papers presented together with 14 technical communications, 4 doctoral consortium contributions, and 3 keynotes were carefully reviewed and selected from 58 submissions. The conference provides the opportunity to present a wider range of results and ideas that are of interest to the KI audience, including reports about recent own publications, position papers, and previews of ongoing work.
Reasoning Robots
The creation of intelligent robots is surely one of the most exciting and ch- lenginggoals of Arti?cial Intelligence. A robot is, ?rst of all, nothing but an inanimate machine with motors and sensors. In order to bring life to it, the machine needs to be programmed so as to make active use of its hardware c- ponents. This turns a machine into an autonomous robot. Since about the mid nineties of the past century, robot programming has made impressive progress. State-of-the-art robots are able to orient themselves and move around freely in indoor environments or negotiate di?cult outdoor terrains, they can use stereo vision to recognize objects, and they are capable of simple object manipulati...
