Behavior-Based Robotics

ISBN-10: 0262011654

ISBN-13: 9780262011655

Edition: 1998

Authors: Ronald C. Arkin

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Description:

Arkin has written the definitive book on the theory and applications of robots based on biological and psychological models of behaviour. Throughout the text he refers to real machines capable of perception, cognition and action.
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Book details

List price: $93.00
Copyright year: 1998
Publisher: MIT Press
Publication date: 5/29/1998
Binding: Hardcover
Pages: 506
Size: 7.75" wide x 9.50" long x 1.25" tall
Weight: 2.486

Ronald C. Arkin is Professor and Director of the Mobile Robot Laboratory, College of Computing, Georgia Institute of Technology.

Foreword
Preface
Whence Behavior?
Toward Intelligent Robots
Precursors
Cybernetics
Artificial Intelligence
Robotics
The Spectrum Of Robot Control
Deliberative/Hierarchical Control
Reactive Systems
Related Issues
What's Ahead
Animal Behavior
What Does Animal Behavior Offer Robotics?
Neuroscientific Basis For Behavior
Neural Circuity
Brain Structure and Function
Abstract Neuroscientific Models
Schema-Theoretic Methods
Neural Networks
Psychological Basis For Behavior
Ethological Basis For Behavior
Representative Examples Of Bio-Robots
Ant Chemotaxis
Fly Vision
Cockroach Locomotion
Primate Brachiation
Robotic Honeybee
Chapter Summary
Robot Behavior
What Are Robotic Behaviors?
Reactive Systems
A Navigational Example
Basis for Robotic Behavior
Expression Of Behaviors
Stimulus-Response Diagrams
Functional Notation
Finite State Acceptor Diagrams
Formal Methods
RS
Situated Automata
Behavioral Encoding
Discrete Encoding
Continuous Functional Encoding
Assembling Behaviors
Emergent Behavior
Notation
Behavioral Coordination
Competitive Methods
Cooperative Methods
Behavioral Assemblages
Chapter Summary
Behavior-Based Architectures
What Is A Robotic Architecture?
Definitions
Computability
Evaluation Criteria
Organizing Principles
A Foraging Example
Subsumption Architecture
Behaviors in Subsumption
Coordination in Subsumption
Design in Subsumption-Based Reactive Systems
Foraging Example
Evaluation
Subsumption Robots
Motor Schemas
Schema-Based Behaviors
Schema-Based Coordination
Design in Motor Schema-Based Systems
Foraging Example
Evaluation
Schema-Based Robots
Other Architectures
Circuit Architecture
Colony Architecture
Animate Agent Architecture
DAMN
Skill Network Architecture
Other Efforts
Architectural Design Issues
Chapter Summary
Representational Issues for Behavioral Systems
Representational Knowledge
What Is Knowledge?
Characteristics of Knowledge
Representational Knowledge For Behavior-Based Systems
Short-Term Behavioral Memory
Long-Term Memory Maps
Sensor-Derived Cognitive Maps
A Priori Map-Derived Representations
Perceptual Representations
Chapter Summary
Hybrid Deliberative/Reactive Architectures
Why Hybridize?
Biological Evidence In Support Of Hybrid Systems
Traditional Deliberative Planners
Deliberation: To Plan Or Not To Plan?
Layering
Representative Hybrid Architectures
AuRa
Atlantis
Planner-Reactor Architecture
The Procedural Reasoning System
Other Hybrid Architectures
Chapter Summary
Perceptual Basis for Behavior-Based Control
A Break From Tradition
What Does Biology Say?
The Nature of Perceptual Stimuli
Neuroscientific Evidence
Psychological Insights
Affordances
A Modified Action-Perception Cycle
Perception as Communication-An Ethological Stance
A Brief Survey Of Robotic Sensors
Dead Reckoning
Ultrasound
Computer Vision
Laser Scanners
Modular Perception
Perceptual Schemas
Visual Routines
Perceptual Classes
Lightweight Vision
Action And Perception
Action-Oriented Perception
Active Perception
The Role of Attention in Human Visual Processing
Hardware Methods for Focus of Attention
Knowledge-Based Focus-of-Attention Methods
Perceptual Sequencing
Sensor Fusion for Behavior-Based Systems
Representative Examples Of Behavior-Based Perception
Road Following
Visual Tracking
Chapter Summary
Adaptive Behavior
Why Should Robots Learn?
Opportunities For Learning In Behavior-Based Robotics
Reinforcement Learning
Learning to Walk
The Learning Algorithm
Robotic Results
Learning to Push
The Learning Algorithm
Robotic Results
Learning to Shoot
Robotic Results
Learning In Neural Networks
Classical Conditioning
Adaptive Heuristic Critic Learning
Learning New Behaviors Using an Associative Memory
Genetic Algorithms
What Are Genetic Algorithms?
Genetic Algorithms for Learning Behavioral Control
Classifier Systems
On-Line Evolution
Evolving Form Concurrently with Control
Hybrid Genetic/Neural Learning and Control
Fuzzy Behavioral Control
What Is Fuzzy Control?
Fuzzy Behavior-Based Robotic Systems
Flakey
Marge
Learning Fuzzy Rules
Other Types Of Learning
Case-Based Learning
Memory-based Learning
Explanation-Based Learning
Chapter Summary
Social Behavior
Are Two (Or N) Robots Better Than One?
Ethological Considerations
Characterization Of Social Behavior
Reliability
Social Organization
Communication
Spatial Distribution
Congregation
Performance
What Makes A Robotic Team?
Social Organization And Structure
The Nerd Herd
Alliance Architecture
Stagnation Behaviors
Societal Agents
Army Ant Project
Interrobot Communication
The Need for Communication
Communication Range
Communication Content
Guaranteeing Communication
Distributed Perception
Social Learning
Reinforcement Learning
L-Alliance
Tropism System Cognitive Architecture
Learning by Imitation
Case Study: Ugv Demo II
Formation Behaviors
Multiagent Mission Specification
Team Teleautonomy
Chapter Summary
Fringe Robotics: Beyond Behavior
Issues Of The Robot Mind
On Computational Thought
On Consciousness
On Emotions
On Imagination
Issues Of The Robot Body
Hormones and Homeostasis
The Homeostat
Subsumption-Based Hormonal Control
Immune Systems
Nanotechnology
On Equivalence (Or Better)
Opportunities
Chapter Summary
References
Name Index
Subject Index
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