rl-softmax-policy 0.1.0

Softmax-based (Boltzmann) action selection strategy for Reinforcement Learning.

rl-softmax-policy

Implements Softmax (Boltzmann) Action Selection, a probabilistic exploration strategy for Reinforcement Learning agents.

Example Usage

from rlsoftmaxpolicy_colab import softmax_action_selection

q_values = [1.0, 2.0, 3.0]
temperature = 0.8
action = softmax_action_selection(q_values, temperature)
print('Selected action:', action)

Author: Afi Prasla