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Introduction

Commonsense reasoning is a fundamental aspect of human cognition that allows individuals to make inferences, draw conclusions, and navigate the complexities of everyday life based on a set of shared beliefs and assumptions. Unlike formal logic, which relies on strict rules and a formalized language, commonsense reasoning is intuitive and often based on implicit knowledge acquired through experience and social interactions. As such, it plays a crucial role in various cognitive tasks, including language understanding, decision-making, and problem-solving.

This thesis aims to explore the concept of commonsense reasoning and its importance in artificial intelligence and cognitive science. By examining existing literature, developing a system design and methodology, implementing a system, and drawing conclusions, this study seeks to contribute to the understanding of how humans reason and how this process can be replicated in machines.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objectives of Study
1.5 Limitations of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter 2: Literature Review
2.1 Overview of Commonsense Reasoning
2.2 Historical Perspectives on Commonsense Reasoning
2.3 Theories of Commonsense Reasoning
2.4 Applications of Commonsense Reasoning in Artificial Intelligence
2.5 Challenges in Commonsense Reasoning
2.6 Current Research in Commonsense Reasoning
2.7 Evaluation Metrics for Commonsense Reasoning Systems
2.8 Comparison of Different Approaches to Commonsense Reasoning
2.9 Future Directions in Commonsense Reasoning Research
2.10 Summary of Literature Review

Chapter 3: System Design and Methodology
3.1 System Architecture
3.2 Data Collection and Annotation
3.3 Feature Extraction
3.4 Modeling Commonsense Reasoning Tasks
3.5 Evaluation Framework
3.6 Experiment Design
3.7 Implementation Details
3.8 Ethical Considerations

Chapter 4: System Implementation
4.1 System Development Process
4.2 Integration of Components
4.3 Testing and Validation
4.4 Optimization Techniques
4.5 Performance Evaluation
4.6 Case Studies
4.7 User Feedback
4.8 System Deployment

Chapter 5: Conclusion
5.1 Summary of Findings
5.2 Contributions to the Field
5.3 Implications for Future Research
5.4 Limitations and Future Work

Thesis Overview on Commonsense Reasoning for General Understanding

Commonsense reasoning is a crucial aspect of human cognition that enables individuals to navigate the complexities of everyday life. Unlike formal logic, which relies on strict rules and a formalized language, commonsense reasoning is intuitive and based on implicit knowledge acquired through experience and social interactions.

This thesis aims to explore the concept of commonsense reasoning and its importance in artificial intelligence and cognitive science. By conducting a comprehensive literature review, developing a system design and methodology, implementing a commonsense reasoning system, and drawing conclusions, this study seeks to contribute to the understanding of how humans reason and how this process can be replicated in machines.

Through an in-depth analysis of existing research, the thesis will provide insights into the historical perspectives, theories, applications, challenges, and current trends in commonsense reasoning. The study will also present a detailed overview of the system design and methodology, including data collection, feature extraction, modeling, evaluation, and experiment design.

Furthermore, the thesis will describe the system implementation process, including system development, integration, testing, optimization, performance evaluation, case studies, user feedback, and deployment. Finally, the conclusion will summarize the findings, discuss contributions to the field, suggest implications for future research, and identify limitations and areas for future work in commonsense reasoning.

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