LNAI 2801 Controlling a Simulated Khepera with an XCS Classifier System with Memory 1st Edition by Andrew Webb, Emma Hart, Peter Ross, Alistair Lawson ISBN 9783540200574 354020057X

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Product details:
ISBN 10: 354020057X
ISBN 13: 9783540200574
Author: Andrew Webb, Emma Hart, Peter Ross, Alistair Lawson

Autonomous agents commonly suffer from perceptual aliasing in which differing situations are perceived as identical by the robots sensors, yet require different courses of action. One technique for addressing this problem is to use additional internal states within a reinforcement learning system, in particular a learning classifier system. Previous research has shown that adding internal memory states can allow an animat within a cellular world to successfully navigate complex mazes. However, the technique has not previously been applied to robotic environments in which sensory data is noisy and somewhat unpredictable. We present results of using XCS with additional internal memory in the simulated Khepera environment, and show that control rules can be evolved to allow the robot to navigate a variety of problems.

LNAI 2801 Controlling a Simulated Khepera with an XCS Classifier System with Memory 1st Edition Table of contents:

Chapter 1: Introduction to Khepera Robots

• Overview of the Khepera Robot
• Features and Capabilities of the Khepera Platform
• Application Areas of the Khepera Robot in Robotics Research
• Simulating the Khepera Robot in Virtual Environments

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Chapter 2: Introduction to XCS Classifier Systems

• What is an XCS Classifier System?
• The Structure of XCS and Its Components
• Learning and Adaptation in XCS Systems
• Advantages of Using XCS in Autonomous Systems

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Chapter 3: Memory in Classifier Systems

• The Role of Memory in Artificial Intelligence Systems
• Memory Mechanisms in XCS Classifier Systems
• How Memory Improves the Performance of XCS
• Challenges and Opportunities in Memory-Enhanced Classifiers

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Chapter 4: Combining XCS with Khepera Robotics

• The Integration of XCS with Khepera Robots
• Design and Architecture of the System
• Communication Between the Classifier System and Robot Sensors
• Challenges of Implementing XCS on the Khepera Platform

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Chapter 5: Theoretical Foundations of XCS with Memory

• Understanding the Memory Extension in XCS
• How Memory Affects the Learning Process in Classifiers
• Theoretical Models for XCS and Memory Integration
• Potential Benefits for Autonomous Robotic Control

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Chapter 6: Implementation of XCS on Khepera Robots

• Step-by-Step Guide to Implementing XCS on the Khepera Platform
• Details of the Software Architecture Used in the Simulation
• Integration of Sensors and Actuators with the XCS System
• Tuning and Configuring the XCS Parameters for Optimal Performance

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Chapter 7: Performance Evaluation

• Metrics for Evaluating Robot Performance
• Experiment Setup and Methodology
• Results from Simulations Using the XCS Classifier System
• Comparison with Other Control Methods for Khepera Robots

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Chapter 8: Memory in Action: Experimental Results

• Case Studies and Experimental Results of XCS with Memory
• Impact of Memory on the Learning and Decision-Making Process
• Performance Enhancement with the Addition of Memory in XCS
• Analysis of Robot Behavior and Task Success Rates

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Chapter 9: Applications and Implications of XCS with Memory

• Practical Applications of XCS with Memory in Robotics
• Potential Uses in Autonomous Navigation and Exploration
• The Future of Memory-Enhanced Classifier Systems in Robotics
• Applications Beyond the Khepera Platform

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Chapter 10: Challenges and Future Directions

• Current Challenges in Implementing Memory in XCS
• Addressing Real-World Constraints in Robotic Control Systems
• Future Developments in Classifier Systems and Memory
• Open Problems and Research Directions for Memory in Autonomous Systems

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Conclusion

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