Structure and Inference in Classical Planning

Structure and Inference in Classical Planning PDF Author: Nir Lipovetzky
Publisher: Lulu.com
ISBN: 1312466219
Category : Computers
Languages : en
Pages : 180

Book Description
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.

A Concise Introduction to Models and Methods for Automated Planning

A Concise Introduction to Models and Methods for Automated Planning PDF Author: Hector Radanovic
Publisher: Springer Nature
ISBN: 3031015649
Category : Computers
Languages : en
Pages : 132

Book Description
Planning is the model-based approach to autonomous behavior where the agent behavior is derived automatically from a model of the actions, sensors, and goals. The main challenges in planning are computational as all models, whether featuring uncertainty and feedback or not, are intractable in the worst case when represented in compact form. In this book, we look at a variety of models used in AI planning, and at the methods that have been developed for solving them. The goal is to provide a modern and coherent view of planning that is precise, concise, and mostly self-contained, without being shallow. For this, we make no attempt at covering the whole variety of planning approaches, ideas, and applications, and focus on the essentials. The target audience of the book are students and researchers interested in autonomous behavior and planning from an AI, engineering, or cognitive science perspective. Table of Contents: Preface / Planning and Autonomous Behavior / Classical Planning: Full Information and Deterministic Actions / Classical Planning: Variations and Extensions / Beyond Classical Planning: Transformations / Planning with Sensing: Logical Models / MDP Planning: Stochastic Actions and Full Feedback / POMDP Planning: Stochastic Actions and Partial Feedback / Discussion / Bibliography / Author's Biography

Machine Learning Methods for Planning

Machine Learning Methods for Planning PDF Author: Steven Minton
Publisher: Morgan Kaufmann
ISBN: 1483221172
Category : Social Science
Languages : en
Pages : 555

Book Description
Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning. Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credit assignment and describe tractable classes of problems for which optimal plans can be derived. This book discusses as well how reactive, integrated systems give rise to new requirements and opportunities for machine learning. The final chapter deals with a method for learning problem decompositions, which is based on an idealized model of efficiency for problem-reduction search. This book is a valuable resource for production managers, planners, scientists, and research workers.

Information Theory, Inference and Learning Algorithms

Information Theory, Inference and Learning Algorithms PDF Author: David J. C. MacKay
Publisher: Cambridge University Press
ISBN: 9780521642989
Category : Computers
Languages : en
Pages : 694

Book Description
Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

Logics in Artificial Intelligence

Logics in Artificial Intelligence PDF Author: Eduardo Fermé
Publisher: Springer
ISBN: 3319115588
Category : Computers
Languages : en
Pages : 719

Book Description
This book constitutes the proceedings of the 14th European Conference on Logics in Artificial Intelligence, JELIA 2014, held in Funchal, Madeira, Portugal, in September 2014. The 35 full papers and 14 short papers included in this volume were carefully reviewed and selected from 121 submissions. They are organized in topical sections named: description logics; automated reasoning; logics for uncertain reasoning; non-classical logics; answer-set programming; belief revision; dealing with inconsistency in ASP and DL; reason about actions and causality; system descriptions; short system descriptions; and short papers. The book also contains 4 full paper invited talks.

An Introduction to the Planning Domain Definition Language

An Introduction to the Planning Domain Definition Language PDF Author: Patrik Haslum
Publisher: Morgan & Claypool Publishers
ISBN: 1627057374
Category : Computers
Languages : en
Pages : 189

Book Description
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 systems comparison, it has become a de-facto standard input language of many planning systems, although it is not the only modelling language for planning. Several variants of PDDL have emerged that capture planning problems of different natures and complexities, with a focus on deterministic problems. The purpose of this book is two-fold. First, we present a unified and current account of PDDL, covering the subsets of PDDL that express discrete, numeric, temporal, and hybrid planning. Second, we want to introduce readers to the art of modelling planning problems in this language, through educational examples that demonstrate how PDDL is used to model realistic planning problems. The book is intended for advanced students and researchers in AI who want to dive into the mechanics of AI planning, as well as those who want to be able to use AI planning systems without an in-depth explanation of the algorithms and implementation techniques they use.

Model Checking and Artificial Intelligence

Model Checking and Artificial Intelligence PDF Author: Ron van der Meyden
Publisher: Springer Science & Business Media
ISBN: 3642206735
Category : Computers
Languages : en
Pages : 139

Book Description
This book presents revised versions of selected papers from the 6th Workshop on Model Checking and Artificial Intelligence, MoChArt 2010, held in Atlanta, GA, USA in July 2010, as well as papers contributed subsequent to the workshop. The 7 papers presented were carefully reviewed and selected for inclusion in this book. In addition, the book also contains an extended abstract of the invited talk held at the workshop. The topics covered by these papers are general search algorithms, application of AI techniques to automated program verification, multiagent systems and epistemic logic, abstraction, epistemic model checking, and theory of model checking.

Discovery Science

Discovery Science PDF Author: João Gama
Publisher: Springer Science & Business Media
ISBN: 3642047467
Category : Computers
Languages : en
Pages : 487

Book Description
This book constitutes the refereed proceedings of the twelfth International Conference, on Discovery Science, DS 2009, held in Porto, Portugal, in October 2009. The 35 revised full papers presented were carefully selected from 92 papers. The scope of the conference includes the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their applications.

Interdisciplinary Approaches to the Structure and Performance of Interdependent Autonomous Human Machine Teams and Systems (A-HMT-S)

Interdisciplinary Approaches to the Structure and Performance of Interdependent Autonomous Human Machine Teams and Systems (A-HMT-S) PDF Author: William Frere Lawless
Publisher: Frontiers Media SA
ISBN: 283251930X
Category : Science
Languages : en
Pages : 220

Book Description


Springer Handbook of Robotics

Springer Handbook of Robotics PDF Author: Bruno Siciliano
Publisher: Springer Science & Business Media
ISBN: 354023957X
Category : Technology & Engineering
Languages : en
Pages : 1626

Book Description
With the science of robotics undergoing a major transformation just now, Springer’s new, authoritative handbook on the subject couldn’t have come at a better time. Having broken free from its origins in industry, robotics has been rapidly expanding into the challenging terrain of unstructured environments. Unlike other handbooks that focus on industrial applications, the Springer Handbook of Robotics incorporates these new developments. Just like all Springer Handbooks, it is utterly comprehensive, edited by internationally renowned experts, and replete with contributions from leading researchers from around the world. The handbook is an ideal resource for robotics experts but also for people new to this expanding field.