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Chapter 1: Introduction to AI Agents
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1.1 What is Artificial Intelligence?
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1.2 What is an AI Agent?
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1.3 Types of AI Agents
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1.4 Characteristics of AI Agents
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Chapter 2 : Simple Reflex Agents
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2.1 Definition
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2.2 Example: Thermostat
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2.3 Advantages and Limitations
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2.4 Limitations
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Chapter 3: Model-Based Reflex Agents
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3.1 Definition
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3.2 Example: Robot Vacuum
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3.3 Why Internal State Matters
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Chapter 4 : Goal-Based Agents
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4.1 Definition
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4.2 Example: Navigation
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4.3 Goal-Based Reasoning
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4.4 Understanding Goal-Based Systems
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4.5 Problem Solving using Goals
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4.6 Real-world Applications
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Chapter 5 : Utility-Based Agents
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5.1 Why Do We Need Utility?
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5.2 Definition
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5.3 Example
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5.4 Decision Making with Utilities
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5.5 Optimal Solutions
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5.6 Utility Theory in AI
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Chapter 6 : Learning Agents
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6.1 Definition
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6.2 Example: Recommendation System
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6.3 Learning from Feedback
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6.4 Reinforcement Learning
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6.5 Machine Learning for AI Agents
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6.6 Types of Learning in AI
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Chapter 7 : Planning Agents
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7.1 Definition
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7.2 Examples
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Chapter 8 : Autonomous AI Agents
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8.1 Definition
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8.2 Agentic Loop
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Chapter 9 : Tool-Using AI Agents
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9.1 Tools
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Chapter 10 : Memory in AI Agents
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10.1 Memory
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Chapter 11 : Multi-Agent Systems
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11.1 Definition
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11.2 Example
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Chapter 12: Modern LLM-Based Agents
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12.1 LLM
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Chapter 13: AI Agent vs Chatbot
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13.1 Conversation Vs Objective
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Chapter 14: Comparison of Agent Types
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14.1 Comparison
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Chapter 15: Real-World Example
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15.1 Example
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Chapter 16: How to Design an AI Agent
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16.1 Design
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Chapter 17: The Complete AI Agent Model
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17.1 Ai Agent Model
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Chapter 18 : Final Understanding
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Idea
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