Implemented AdaTD and compared it with other optimization methods in temporal difference learning. Used in the paper Adaptive Temporal Difference Learning with Linear Function Approximation.
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Dependencies: Python (3.7.3), OpenAI gym (0.10.5), numpy (1.14.5), matplotlib (3.0.3), tensorflow (2.0.0), multiagent
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To install dpendency 'multiagent': Download 'multiagent-particle-envs-master' provided in folder 'AdaTD-master'. Then cd into its root directory and install it using 'pip install -e multiagent-particle-envs-master'
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optimizers_linear.py: Code for running AdaTD, ALRR-TD, and vanilla-TD simultaneously under linear value function approximation. -
optimzers_nonlinear.py: Code for running AdaTD and vanilla-TD simultaneously under nonlinear value function approximation.
The dependency 'multiagent' used in this repo is a modified version of Multi-Agent Particle Environment