close
1.

図書
図書
1. 9th IFAC Symposium on Intelligent Autonomous Vehicles (IAV 2016) : Leipzig, Germany 29 June-1 July 2016 (: pbk)
editor, Raul Rojas
出版情報: New York : Elsevier , Red Hook, NY : Printed from e-media with permission by Curran Associates, 2016  271 p. ; 27 cm
シリーズ名: IFAC PapersOnline ; v. 49, issue 15
2.

図書
図書
2. 11th IFAC Symposium on Intelligent Autonomous Vehicles (IAV 2022) : Prague, Czech Republic 6-8 July 2022 (: pbk)
editors, Miroslav Kulich, Karel Kosnar, Libor Preucil
出版情報: Oxford : Elsevier , Red Hook, NY : Printed with permission by Curran Associates, 2022  157 p. ; 28 cm
シリーズ名: IFAC PapersOnline ; v. 55, issue 14
3.

図書
図書
3. 10th IFAC Symposium on Intelligent Autonomous Vehicles (IAV 2019) : Gdansk, Poland 3-5 July 2019 (: pbk)
editors, Bogdan Wiszniewski, Zdzislaw Kowalczuk, Mariusz Domzalski
出版情報: Oxford : Elsevier , Red Hook, NY : Printed from e-media with permission by Curran Associates, 2020, c2019  473 p. ; 28 cm
シリーズ名: IFAC PapersOnline ; v. 52, issue 8
4.

図書
図書
4. Behavior-based robotics
Ronald C. Arkin
出版情報: Cambridge, Mass. ; London, England : MIT Press, c1998  xiv, 491 p. ; 24 cm
シリーズ名: Intelligent robotics and autonomous agents
目次情報: 続きを見る
Foreword
Preface
Whence Behavior? / Chapter 1：
Toward Intelligent Robots / 1.1：
Precursors / 1.2：
Cybernetics / 1.2.1：
Artificial Intelligence / 1.2.2：
Robotics / 1.2.3：
The Spectrum Of Robot Control / 1.3：
Deliberative/Hierarchical Control / 1.3.1：
Reactive Systems / 1.3.2：
Related Issues / 1.4：
What's Ahead / 1.5：
Animal Behavior / Chapter 2：
What Does Animal Behavior Offer Robotics? / 2.1：
Neuroscientific Basis For Behavior / 2.2：
Neural Circuity / 2.2.1：
Brain Structure and Function / 2.2.2：
Abstract Neuroscientific Models / 2.2.3：
Schema-Theoretic Methods / 2.2.3.1：
Neural Networks / 2.2.3.2：
Psychological Basis For Behavior / 2.3：
Ethological Basis For Behavior / 2.4：
Representative Examples Of Bio-Robots / 2.5：
Ant Chemotaxis / 2.5.1：
Fly Vision / 2.5.2：
Cockroach Locomotion / 2.5.3：
Primate Brachiation / 2.5.4：
Robotic Honeybee / 2.5.5：
Chapter Summary / 2.6：
Robot Behavior / Chapter 3：
What Are Robotic Behaviors? / 3.1：
A Navigational Example / 3.1.1：
Basis for Robotic Behavior / 3.1.3：
Expression Of Behaviors / 3.2：
Stimulus-Response Diagrams / 3.2.1：
Functional Notation / 3.2.2：
Finite State Acceptor Diagrams / 3.2.3：
Formal Methods / 3.2.4：
RS / 3.2.4.1：
Situated Automata / 3.2.4.2：
Behavioral Encoding / 3.3：
Discrete Encoding / 3.3.1：
Continuous Functional Encoding / 3.3.2：
Assembling Behaviors / 3.4：
Emergent Behavior / 3.4.1：
Notation / 3.4.2：
Behavioral Coordination / 3.4.3：
Competitive Methods / 3.4.3.1：
Cooperative Methods / 3.4.3.2：
Behavioral Assemblages / 3.4.4：
Behavior-Based Architectures / 3.5：
What Is A Robotic Architecture? / 4.1：
Definitions / 4.1.1：
Computability / 4.1.2：
Evaluation Criteria / 4.1.3：
Organizing Principles / 4.1.4：
A Foraging Example / 4.2：
Subsumption Architecture / 4.3：
Behaviors in Subsumption / 4.3.1：
Coordination in Subsumption / 4.3.2：
Design in Subsumption-Based Reactive Systems / 4.3.3：
Foraging Example / 4.3.4：
Evaluation / 4.3.5：
Subsumption Robots / 4.3.6：
Motor Schemas / 4.4：
Schema-Based Behaviors / 4.4.1：
Schema-Based Coordination / 4.4.2：
Design in Motor Schema-Based Systems / 4.4.3：
Schema-Based Robots / 4.4.4：
Other Architectures / 4.5：
Circuit Architecture / 4.5.1：
Colony Architecture / 4.5.3：
Animate Agent Architecture / 4.5.4：
DAMN / 4.5.5：
Skill Network Architecture / 4.5.6：
Other Efforts / 4.5.7：
Architectural Design Issues / 4.6：
Representational Issues for Behavioral Systems / 4.7：
Representational Knowledge / 5.1：
What Is Knowledge? / 5.1.1：
Characteristics of Knowledge / 5.1.2：
Representational Knowledge For Behavior-Based Systems / 5.2：
Short-Term Behavioral Memory / 5.2.1：
Long-Term Memory Maps / 5.2.2：
Sensor-Derived Cognitive Maps / 5.2.2.1：
A Priori Map-Derived Representations / 5.2.2.2：
Perceptual Representations / 5.3：
Hybrid Deliberative/Reactive Architectures / 5.4：
Why Hybridize? / 6.1：
Biological Evidence In Support Of Hybrid Systems / 6.2：
Traditional Deliberative Planners / 6.3：
Deliberation: To Plan Or Not To Plan? / 6.4：
Layering / 6.5：
Representative Hybrid Architectures / 6.6：
AuRa / 6.6.1：
Atlantis / 6.6.2：
Planner-Reactor Architecture / 6.6.3：
The Procedural Reasoning System / 6.6.4：
Other Hybrid Architectures / 6.6.5：
Perceptual Basis for Behavior-Based Control / 6.7：
A Break From Tradition / 7.1：
What Does Biology Say? / 7.2：
The Nature of Perceptual Stimuli / 7.2.1：
Neuroscientific Evidence / 7.2.2：
Psychological Insights / 7.2.3：
Affordances / 7.2.3.1：
A Modified Action-Perception Cycle / 7.2.3.2：
Perception as Communication-An Ethological Stance / 7.2.4：
A Brief Survey Of Robotic Sensors / 7.3：
Dead Reckoning / 7.3.1：
Ultrasound / 7.3.2：
Computer Vision / 7.3.3：
Laser Scanners / 7.3.4：
Modular Perception / 7.4：
Perceptual Schemas / 7.4.1：
Visual Routines / 7.4.2：
Perceptual Classes / 7.4.3：
Lightweight Vision / 7.4.4：
Action And Perception / 7.5：
Action-Oriented Perception / 7.5.1：
Active Perception / 7.5.2：
The Role of Attention in Human Visual Processing / 7.5.5.1：
Hardware Methods for Focus of Attention / 7.5.5.2：
Knowledge-Based Focus-of-Attention Methods / 7.5.5.3：
Perceptual Sequencing / 7.5.6：
Sensor Fusion for Behavior-Based Systems / 7.5.7：
Representative Examples Of Behavior-Based Perception / 7.6：
Road Following / 7.6.1：
Visual Tracking / 7.6.2：
Adaptive Behavior / 7.7：
Why Should Robots Learn? / 8.1：
Opportunities For Learning In Behavior-Based Robotics / 8.2：
Reinforcement Learning / 8.3：
Learning to Walk / 8.3.1：
The Learning Algorithm / 8.3.1.1：
Robotic Results / 8.3.1.2：
Learning to Push / 8.3.2：
Learning to Shoot / 8.3.2.1：
Learning In Neural Networks / 8.3.3.1：
Classical Conditioning / 8.4.1：
Adaptive Heuristic Critic Learning / 8.4.2：
Learning New Behaviors Using an Associative Memory / 8.4.3：
Genetic Algorithms / 8.5：
What Are Genetic Algorithms? / 8.5.1：
Genetic Algorithms for Learning Behavioral Control / 8.5.2：
Classifier Systems / 8.5.3：
On-Line Evolution / 8.5.4：
Evolving Form Concurrently with Control / 8.5.5：
Hybrid Genetic/Neural Learning and Control / 8.5.6：
Fuzzy Behavioral Control / 8.6：
What Is Fuzzy Control? / 8.6.1：
Fuzzy Behavior-Based Robotic Systems / 8.6.2：
Flakey / 8.6.2.1：
Marge / 8.6.2.2：
Learning Fuzzy Rules / 8.6.3：
Other Types Of Learning / 8.7：
Case-Based Learning / 8.7.1：
Memory-based Learning / 8.7.2：
Explanation-Based Learning / 8.7.3：
Social Behavior / 8.8：
Are Two (Or N) Robots Better Than One? / 9.1：
Ethological Considerations / 9.2：
Characterization Of Social Behavior / 9.3：
Reliability / 9.3.1：
Social Organization / 9.3.2：
Communication / 9.3.3：
Spatial Distribution / 9.3.4：
Congregation / 9.3.5：
Performance / 9.3.6：
What Makes A Robotic Team? / 9.4：
Social Organization And Structure / 9.5：
The Nerd Herd / 9.5.1：
Alliance Architecture / 9.5.2：
Stagnation Behaviors / 9.5.3：
Societal Agents / 9.5.4：
Army Ant Project / 9.5.5：
Interrobot Communication / 9.6：
The Need for Communication / 9.6.1：
Communication Range / 9.6.2：
Communication Content / 9.6.3：
Guaranteeing Communication / 9.6.4：
Distributed Perception / 9.7：
Social Learning / 9.8：
L-Alliance / 9.8.1：
Tropism System Cognitive Architecture / 9.8.3：
Learning by Imitation / 9.8.4：
Case Study: Ugv Demo II / 9.9：
Formation Behaviors / 9.9.1：
Multiagent Mission Specification / 9.9.2：
Team Teleautonomy / 9.9.3：
Fringe Robotics: Beyond Behavior / 9.10：
Issues Of The Robot Mind / 10.1：
On Computational Thought / 10.1.1：
On Consciousness / 10.1.2：
On Emotions / 10.1.3：
On Imagination / 10.1.4：
Issues Of The Robot Body / 10.2：
Hormones and Homeostasis / 10.2.1：
The Homeostat / 10.2.1.1：
Subsumption-Based Hormonal Control / 10.2.1.3：
Immune Systems / 10.2.2：
Nanotechnology / 10.2.3：
On Equivalence (Or Better) / 10.3：
Opportunities / 10.4：
References / 10.5：
Name Index
Subject Index
Foreword
Preface
Whence Behavior? / Chapter 1：
5.

図書
図書
5. Plan-based control of robotic agents : improving the capabilities of autonomous robots
Michael Beetz
出版情報: Berlin ; Tokyo : Springer, c2002  xi, 191 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 2554 . Lecture notes in artificial intelligence
目次情報: 続きを見る
Introduction / 1：
The Challenges of Controlling Robot Office Couriers / 1.1：
The Control Problem / 1.2：
The Computational Model / 1.3：
An Adaptive Robotic Office Courier / 1.4：
Previous Work / 1.5：
Descriptive Models of Everyday Activity / 1.5.1：
Computational Models of Everyday Activity / 1.5.2：
Contributions / 1.6：
Overview / 1.7：
Overview of the Control System / 2：
Abstract Models of Robotic Agents / 2.1：
The Dynamic System Model / 2.1.1：
Autonomous Robots as Rational Agents / 2.1.2：
The BDI Model of Rational Agents / 2.1.3：
Discussion of Our Robotic Agent Model / 2.1.4：
The Environment Maps / 2.2：
The Computational Structure of the Control System / 2.3：
The Functional Layer / 2.3.1：
The "Robotic Agent" Abstract Machine / 2.3.2：
The Structured Reactive Controller / 2.3.3：
Plan Representation for Robotic Agents / 3：
Low -Level Integration of Mechanisms / 3.1：
Navigation / 3.1.1：
Communication Mechanisms / 3.1.2：
Execution Time Planning / 3.1.3：
Image Processing / 3.1.4：
Summary of Low -Level Integration / 3.1.5：
Low -Level Plans / 3.2：
Low -Level Navigation Plans / 3.2.1：
Low -Level Image Processing Plans / 3.2.2：
Low -Level Conversational Plans / 3.2.3：
Task-Specific Low -Level Plans / 3.2.4：
Summary of Low -Level Plans / 3.2.5：
Structured Reactive Plans / 3.3：
Properties of SRCs and Their Sub-plans / 3.3.1：
High-Level Navigation Plans / 3.3.2：
Structured Reactive Plans for Other Mechanisms / 3.3.3：
The Plan Adaptation Framew ork / 3.4：
Properties of Revision Rules and Revisable Plans / 3.4.1：
Revision Rules / 3.4.2：
Related Work on Plan Representation / 3.5：
Discussion / 3.6：
Probabilistic Hybrid Action Models / 4：
Projecting Delivery Tour Plans / 4.1：
Modeling Reactive Control Processes and Continuous Change / 4.2：
Probabilistic, Totally-Ordered Temporal Projection / 4.3：
Probabilistic Temporal Rules for PHAMs / 4.3.1：
Properties of PHAMs / 4.3.2：
The Implementation of PHAMs / 4.4：
Projection with Adaptive Causal Models / 4.4.1：
Endogenous Event Scheduler / 4.4.2：
Projecting Exogenous Events, Passive Sensors, and Obstacle Avoidance / 4.4.3：
Probabilistic Sampling-Based Projection / 4.4.4：
Evaluation / 4.5：
Generality / 4.5.1：
Scaling Up / 4.5.2：
Qualitatively Accurate Predictions / 4.5.3：
Related Work on Temporal Projection / 4.6：
LearningStructured Reactive Navigation Plans / 4.7：
Navigation Planning as a Markov Decision Problem / 5.1：
An Overviewon XfrmLearn / 5.2：
Structured Reactive Navigation Plans / 5.3：
XfrmLearn in Detail / 5.4：
The "Analyze" Step / 5.4.1：
The "Revise" Step / 5.4.2：
The "Test" Step / 5.4.3：
Experimental Results / 5.5：
The First Learning Experiment / 5.5.1：
The Second Learning Experiment / 5.5.2：
Discussion of the Experiments / 5.5.3：
Related Work on Learning Robot Plans / 5.6：
Plan-Based Robotic Agents / 5.7：
A Robot Office Courier / 6.1：
The Plans of the Robot Courier / 6.1.1：
Plan Adaptors of the Robot Courier / 6.1.2：
Probabilistic Prediction-Based Schedule Debugging / 6.1.3：
Demonstrations and Experiments / 6.1.4：
Prediction-Based Plan Management / 6.1.5：
A Robot Museums Tourguide / 6.2：
The Plans of the Tourguide Robot / 6.2.1：
Learning Tours and Tour Management / 6.2.2：
Demonstrations of the Tourguide Robot / 6.2.3：
A Robot Party Butler / 6.3：
Demonstrations of Integrated Mechanisms / 6.4：
Communication / 6.4.1：
Resource-Adaptive Search / 6.4.2：
Active Localization / 6.4.4：
Related Work on Plan-Based Robotic Agents / 6.5：
XAVIER / 6.5.1：
CHIP / 6.5.2：
Flakey / 6.5.3：
An Architecture for Autonomy / 6.5.4：
Remote Agent / 6.5.5：
Conclusions / 6.6：
Bibliography
Introduction / 1：
The Challenges of Controlling Robot Office Couriers / 1.1：
The Control Problem / 1.2：
6.

図書
図書
6. Intelligent autonomous vehicles 2001 (IAV 2001) : a proceedings volume from the 4th IFAC Symposium, Sapporo, Japan, 5-7 September 2001
edited by H. Asama and H. Inoue
出版情報: Oxford : Published for the International Federation of Automatic Control by Pergamon, 2002  viii, 411 p. ; 30 cm
7.

図書
図書
7. Intelligent autonomous vehicles 2004 (IAV 2004) : a proceedings volume from the 5th IFAC-EURON Symposium, Lisbon, Portugal, 5-7 July 2004 (vol. 1 ; vol. 2)
edited by J. Santos-Victor and M. I. Ribeiro
出版情報: Oxford : Published for the International Federation of Automatic Control by Elsevier, 2005  2 v. (xv, 967 p.) ; 30 cm
8.

図書
図書
8. 8th IFAC Symposium on Intelligent Autonomous Vehicles 2013 : Gold Coast, Australia, 26-28 June 2013 (: pbk)
editors, Ljubo Vlacic, Stefan Jakubek, Giovanni Indiveri
出版情報: Oxford, UK : Elsevier , Red Hook, NY : Printed from e-media with permission by Curran Associates, 2013  297 p. ; 27 cm
9.

図書
図書
9. 7th IFAC symposium on intelligent autonomous vehicles 2010 ; Lecce, Italy 6-8 September 2010
editors, Giovanni Indiveri, António M. Pascoal
出版情報: Oxford, UK : Elsevier, c2010  628 p. ; 27 cm
10.

図書
図書
10. 6th IFAC symposium on intelligent autonomous vehicles 2007 ; Toulouse, France 3-5 September 2007
editor,
出版情報: Oxford, UK : Elsevier, c2010  565 p. ; 27 cm
文献の複写および貸借の依頼を行う
 文献複写・貸借依頼