semvec/pypi-packages huggingface dataset:
rl-softmax-policy 0.1.0
Softmax-based (Boltzmann) action selection strategy for Reinforcement Learning.
License: MIT
Requires Python: >=3.8
Keywords: boltzmann, policy, reinforcement-learning, rl, softmax

# rl-softmax-policy

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

## Example Usage
```python
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