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README.md

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@@ -12,18 +12,33 @@ It provides clean, minimal, and well-tested implementations of key reinforcement
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```
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rl-fundamentals-code/
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├─ ch2_rl_formulation/ # Chapter 2: The RL Problem Formulation
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│ ├─ gridworld.py # 4x4 GridWorld MDP
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│ ├─ evaluation.py # Policy evaluation, q_from_v
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│ ├─ policies.py # Greedy & ε-greedy policies
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│ ├─ examples/ # Numeric examples + GridWorld demo
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│ └─ tests/ # Pytest-based validation
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├─ ch3_multi_armed_bandits/ # Chapter 3: Multi-Armed Bandits (placeholder)
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│ └─ tests/
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├─ utils/ # Shared helper utilities
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├─ .github/workflows/ # CI: runs PyTest on every push/PR
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├─ requirements.txt # Global dependencies
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└─ README.md
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├─ ch2_rl_formulation/ # Chapter 2: The RL Problem Formulation
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│ ├─ gridworld.py # 4x4 GridWorld MDP (tabular P,R builder)
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│ ├─ evaluation.py # Policy evaluation, q_from_v(), greedy_from_q()
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│ ├─ policies.py # Deterministic & ε-greedy policies
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│ ├─ value_iteration.py # Bellman optimality, value iteration
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│ ├─ examples/ # Numeric examples, GridWorld demo, plotting
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│ └─ tests/ # Pytest-based checks for chapter numbers
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├─ ch3_multi_armed_bandits/ # Chapter 3: Multi-Armed Bandits
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│ ├─ bandits.py # Bernoulli & Gaussian bandit environments
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│ ├─ epsilon_greedy.py # Sample-average ε-greedy agent
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│ ├─ ucb.py # UCB1 agent (with tunable exploration constant)
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│ ├─ thompson.py # Beta–Bernoulli Thompson Sampling agent
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│ ├─ experiments.py # Run algorithms, generate regret plots
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│ ├─ plots/ # Saved figures (regret_bernoulli.png, etc.)
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│ └─ tests/ # Regression tests (ordering, sublinear regret)
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├─ utils/ # Shared helper utilities (future use)
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├─ .github/workflows/ # CI: runs pytest on every push/PR
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│ └─ python-tests.yml
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├─ requirements.txt # Global dependencies (numpy, matplotlib, pytest)
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├─ requirements_ch2.txt # Chapter 2–specific dependencies
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├─ requirements_ch3.txt # Chapter 3–specific dependencies
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└─ README.md # Project overview + usage
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```
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