A Concise Introduction To Models And Methods For Automated Planning
DOWNLOAD
Download A Concise Introduction To Models And Methods For Automated Planning PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get A Concise Introduction To Models And Methods For Automated Planning book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
A Concise Introduction To Models And Methods For Automated Planning
DOWNLOAD
Author : Hector Geffner
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2013-06-01
A Concise Introduction To Models And Methods For Automated Planning written by Hector Geffner and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-01 with Computers categories.
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
A Concise Introduction To Models And Methods For Automated Planning
DOWNLOAD
Author : Hector Geffner
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
A Concise Introduction To Models And Methods For Automated Planning written by Hector Geffner and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
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
Ecai 2023
DOWNLOAD
Author : K. Gal
language : en
Publisher: IOS Press
Release Date : 2023-10-18
Ecai 2023 written by K. Gal and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-18 with Computers categories.
Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.
Artificial Intelligence Research And Development
DOWNLOAD
Author : A. Nebot
language : en
Publisher: IOS Press
Release Date : 2016-09-21
Artificial Intelligence Research And Development written by A. Nebot and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-21 with Computers categories.
The Catalan Association for Artificial Intelligence (ACIA) was formed in 1994 with the aim of promoting cooperation between researchers in artificial intelligence within the Catalan speaking community. This objective has been achieved and widened since the association held their first conference in 1998, and the annual conference of the association has become an international event presenting and discussing the latest research in AI, which attracts AI researchers from around the world. This book presents the proceedings of the 19th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2016), held in Barcelona, Spain, on 19-21 October. From a total of 50 original contributions, 16 long papers and 22 short papers were accepted for presentation at the conference on the basis of their relevance, originality and technical validity. The book is divided into 7 sections: Invited Talks (synopsis only); Vision and Robotics; Logic, Constraint Satisfaction and Qualitative Theory; Classification and Clustering; Modelling; Planning and Recommender Systems; Lexical Knowledge Representation and Natural Language Processing. Providing an overview of the latest developments in the field, this book will be of interest to all those whose work involves research into, and the application of, artificial intelligence.
Introduction To Symbolic Plan And Goal Recognition
DOWNLOAD
Author : Reuth Mirsky
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Introduction To Symbolic Plan And Goal Recognition written by Reuth Mirsky and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
Plan recognition, activity recognition, and goal recognition all involve making inferences about other actors based on observations of their interactions with the environment and other agents. This synergistic area of research combines, unites, and makes use of techniques and research from a wide range of areas including user modeling, machine vision, automated planning, intelligent user interfaces, human-computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning. It plays a crucial role in a wide variety of applications including assistive technology, software assistants, computer and network security, human-robot collaboration, natural language processing, video games, and many more. This wide range of applications and disciplines has produced a wealth of ideas, models, tools, and results in the recognition literature. However, it has also contributed to fragmentation in the field, with researchers publishing relevant results in a wide spectrum of journals and conferences. This book seeks to address this fragmentation by providing a high-level introduction and historical overview of the plan and goal recognition literature. It provides a description of the core elements that comprise these recognition problems and practical advice for modeling them. In particular, we define and distinguish the different recognition tasks. We formalize the major approaches to modeling these problems using a single motivating example. Finally, we describe a number of state-of-the-art systems and their extensions, future challenges, and some potential applications.
An Introduction To The Planning Domain Definition Language
DOWNLOAD
Author : Patrik Haslum
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
An Introduction To The Planning Domain Definition Language written by Patrik Haslum and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
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.
Intelligent Systems For Engineers And Scientists
DOWNLOAD
Author : Adrian A. Hopgood
language : en
Publisher: CRC Press
Release Date : 2021-12-09
Intelligent Systems For Engineers And Scientists written by Adrian A. Hopgood and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-09 with Technology & Engineering categories.
The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. Fully updated and revised, Intelligent Systems for Engineers and Scientists: A Practical Guide to Artificial Intelligence, Fourth Edition features: A new chapter on deep neural networks, reflecting the growth of machine learning as a key technique for AI A new section on the use of Python, which has become the de facto standard programming language for many aspects of AI The rule-based and uncertainty-based examples in the book are compatible with the Flex toolkit by Logic Programming Associates (LPA) and its Flint extension for handling uncertainty and fuzzy logic. Readers of the book can download this commercial software for use free of charge. This resource and many others are available at the author’s website: adrianhopgood.com. Whether you are building your own intelligent systems, or you simply want to know more about them, this practical AI textbook provides you with detailed and up-to-date guidance.
Computational Complexity Of Some Optimization Problems In Planning
DOWNLOAD
Author : Meysam Aghighi
language : en
Publisher: Linköping University Electronic Press
Release Date : 2017-05-17
Computational Complexity Of Some Optimization Problems In Planning written by Meysam Aghighi and has been published by Linköping University Electronic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-17 with categories.
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 in order to construct better heuristic functions and improve planners. We identify a new class of tractable cost-optimal planning instances by restricting the causal graph. We study the computational complexity of oversubscription planning (such as the net-benefit problem) under various restrictions and reveal strong connections with classical planning. Inspired by this, we present a method for compiling oversubscription planning problems into the ordinary plan existence problem. We further study the parameterized complexity of cost-optimal and net-benefit planning under the same restrictions and show that the choice of numeric domain for the action costs has a great impact on the parameterized complexity. We finally consider the parameterized complexity of certain problems related to partial-order planning. In some applications, less restricted plans than total-order plans are needed. Therefore, a partial-order plan is being used instead. When dealing with partial-order plans, one important question is how to achieve optimal partial order plans, i.e. having the highest degree of freedom according to some notion of flexibility. We study several optimization problems for partial-order plans, such as finding a minimum deordering or reordering, and finding the minimum parallel execution length.
Advances In Architectural Geometry 2023
DOWNLOAD
Author : Kathrin Dörfler
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2023-10-04
Advances In Architectural Geometry 2023 written by Kathrin Dörfler and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-04 with Computers categories.
This book contains 34 technical papers presented at the Advances in Architectural Geometry Conference held in Stuttgart 2023. Modern geometric computing increasingly plays a role in modeling environments and processing sensing information, providing a variety of tools for the efficient design, analysis, and manufacturing of complex shapes. The research area of architectural geometry (AG) has emerged at the common border of architecture, applied geometry, computational design, mathematics, and manufacturing. This book presents the state of the art of research in AG.
Reasoning With Probabilistic And Deterministic Graphical Models
DOWNLOAD
Author : Rina Kraus
language : en
Publisher: Springer Nature
Release Date : 2022-12-06
Reasoning With Probabilistic And Deterministic Graphical Models written by Rina Kraus and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-06 with Computers categories.
Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reasoning tasks, such as scheduling, planning and learning, diagnosis and prediction, design, hardware and software verification, and bioinformatics. These problems can be stated as the formal tasks of constraint satisfaction and satisfiability, combinatorial optimization, and probabilistic inference. It is well known that the tasks are computationally hard, but research during the past three decades has yielded a variety of principles and techniques that significantly advanced the state of the art. In this book we provide comprehensive coverage of the primary exact algorithms for reasoning with such models. The main feature exploited by the algorithms is the model's graph. We present inference-based, message-passing schemes (e.g., variable-elimination) and search-based, conditioning schemes (e.g., cycle-cutset conditioning and AND/OR search). Each class possesses distinguished characteristics and in particular has different time vs. space behavior. We emphasize the dependence of both schemes on few graph parameters such as the treewidth, cycle-cutset, and (the pseudo-tree) height. We believe the principles outlined here would serve well in moving forward to approximation and anytime-based schemes. The target audience of this book is researchers and students in the artificial intelligence and machine learning area, and beyond.