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Principles of Knowledge Representation and Reasoning
Stringently reviewed papers presented at the October 1992 meeting held in Cambridge, Mass., address such topics as nonmonotonic logic; taxonomic logic; specialized algorithms for temporal, spatial, and numerical reasoning; and knowledge representation issues in planning, diagnosis, and natural langu
Computational Complexity of some Optimization Problems in Planning
Automated planning is known to be computationally hard in the general case. Propositional planning is PSPACE-complete and first-order planning is undecidable. One method for analyzing the computational complexity of planning is to study restricted subsets of planning instances, with the aim of differentiating instances with varying complexity. We use this methodology for studying the computational complexity of planning. Finding new tractable (i.e. polynomial-time solvable) problems has been a particularly important goal for researchers in the area. The reason behind this is not only to differentiate between easy and hard planning instances, but also to use polynomial-time solvable instances...
Principles of Knowledge Representation and Reasoning
The proceedings of KR '94 comprise 55 papers on topics including deduction an search, description logics, theories of knowledge and belief, nonmonotonic reasoning and belief revision, action and time, planning and decision-making and reasoning about the physical world, and the relations between KR
Handbook of Temporal Reasoning in Artificial Intelligence
This collection represents the primary reference work for researchers and students in the area of Temporal Reasoning in Artificial Intelligence. Temporal reasoning has a vital role to play in many areas, particularly Artificial Intelligence. Yet, until now, there has been no single volume collecting together the breadth of work in this area. This collection brings together the leading researchers in a range of relevant areas and provides an coherent description of the breadth of activity concerning temporal reasoning in the filed of Artificial Intelligence.Key Features:- Broad range: foundations; techniques and applications- Leading researchers around the world have written the chapters- Covers many vital applications- Source book for Artificial Intelligence, temporal reasoning- Approaches provide foundation for many future software systems· Broad range: foundations; techniques and applications· Leading researchers around the world have written the chapters· Covers many vital applications· Source book for Artificial Intelligence, temporal reasoning· Approaches provide foundation for many future software systems
An Introduction to the Planning Domain Definition Language
Planning is the branch of Artificial Intelligence (AI) that seeks to automate reasoning about plans, most importantly the reasoning that goes into formulating a plan to achieve a given goal in a given situation. AI planning is model-based: a planning system takes as input a description (or model) of the initial situation, the actions available to change it, and the goal condition to output a plan composed of those actions that will accomplish the goal when executed from the initial situation. The Planning Domain Definition Language (PDDL) is a formal knowledge representation language designed to express planning models. Developed by the planning research community as a means of facilitating ...
ECAI 2016
Artificial Intelligence continues to be one of the most exciting and fast-developing fields of computer science. This book presents the 177 long papers and 123 short papers accepted for ECAI 2016, the latest edition of the biennial European Conference on Artificial Intelligence, Europe’s premier venue for presenting scientific results in AI. The conference was held in The Hague, the Netherlands, from August 29 to September 2, 2016. ECAI 2016 also incorporated the conference on Prestigious Applications of Intelligent Systems (PAIS) 2016, and the Starting AI Researcher Symposium (STAIRS). The papers from PAIS are included in this volume; the papers from STAIRS are published in a separate volume in the Frontiers in Artificial Intelligence and Applications (FAIA) series. Organized by the European Association for Artificial Intelligence (EurAI) and the Benelux Association for Artificial Intelligence (BNVKI), the ECAI conference provides an opportunity for researchers to present and hear about the very best research in contemporary AI. This proceedings will be of interest to all those seeking an overview of the very latest innovations and developments in this field.
Expert Systems in Engineering
The goal of the International Workshop on Expert Systems in Engineering is to stimulate the flow of information between researchers working on theoretical and applied research topics in this area. It puts special emphasis on new technologies relevant to industrial engineering expert systems, such as model-based diagnosis, qualitative reasoning, planning, and design, and to the conditions in which they operate, in real time, with database support. The workshop is especially relevant for engineering environments like CIM (computer integrated manufacturing) and process automation.
Structure and Inference in Classical Planning
Classical planning is the problem of finding a sequence of actions for achieving a goal from an initial state assuming that actions have deterministic effects. The most effective approach for finding such plans is based on heuristic search guided by heuristics extracted automatically from the problem representation. In this thesis, we introduce alternative approaches for performing inference over the structure of planning problems that do not appeal to heuristic functions, nor to reductions to other formalisms such as SAT or CSP. We show that many of the standard benchmark domains can be solved with almost no search or a polynomially bounded amount of search, once the structure of planning problems is taken into account. In certain cases we can characterize this structure in terms of a novel width parameter for classical planning.
Thermal Issues in Testing of Advanced Systems on Chip
Many cutting-edge computer and electronic products are powered by advanced Systems-on-Chip (SoC). Advanced SoCs encompass superb performance together with large number of functions. This is achieved by efficient integration of huge number of transistors. Such very large scale integration is enabled by a core-based design paradigm as well as deep-submicron and 3D-stacked-IC technologies. These technologies are susceptible to reliability and testing complications caused by thermal issues. Three crucial thermal issues related to temperature variations, temperature gradients, and temperature cycling are addressed in this thesis. Existing test scheduling techniques rely on temperature simulations...
