reinforcement-learning-practise

Consists of all solutions to RL problems, implemented independently as part of Final Year Thesis Project, NIT Warangal.

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
BEST. THESIS. EVER.pdf		BEST. THESIS. EVER.pdf
MARL for Q-Learning.pdf		MARL for Q-Learning.pdf
Multiagent Cooperation and Competition with Deep Reinforcement Learning.pdf		Multiagent Cooperation and Competition with Deep Reinforcement Learning.pdf
News Oriented Stock Trading .pdf		News Oriented Stock Trading .pdf
README.md		README.md
Rainbow: Combining Improvements in Deep Reinforcement Learning.pdf		Rainbow: Combining Improvements in Deep Reinforcement Learning.pdf
SARSA.py		SARSA.py
TD0_prediction		TD0_prediction
TD0_prediction.py		TD0_prediction.py
The impact of financial news and public mood on stock movements.pdf		The impact of financial news and public mood on stock movements.pdf
approx_mc_prediction.py		approx_mc_prediction.py
approx_semigradient_sarsa_control.py		approx_semigradient_sarsa_control.py
approx_semigradient_td0_prediction.py		approx_semigradient_td0_prediction.py
grid_world.py		grid_world.py
iterative_policy_evaluation.py		iterative_policy_evaluation.py
monte_carlo.py		monte_carlo.py
monte_carlo_es.py		monte_carlo_es.py
monte_carlo_no_es.py		monte_carlo_no_es.py
monte_carlo_random.py		monte_carlo_random.py
policy_iteration.py		policy_iteration.py
policy_iteration_random.py		policy_iteration_random.py
q-learning-bins.py		q-learning-bins.py
q_learning		q_learning
q_learning.py		q_learning.py
random_search.py		random_search.py
random_search2.py		random_search2.py
value_iteration.py		value_iteration.py

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