MPC - Model Predictive Control
Ver. 1.1.1 (2023-02-04)
This module provides a default implementation of model predictive control (MPC).
- class mlpro.rl.pool.actionplanner.mpc.MPC(p_range_max=0, p_state_thsld=1e-08, p_logging=True)
Bases:
ActionPlanner
,ScientificObject
,Async
Template class for MPC to be used as part of model-based planning agents. The goal is to find the best sequence of actions that leads to a maximum reward.
- Parameters:
p_range (int) – Range of asynchonicity.
p_state_thsld (float) – Threshold for metric difference between two states to be equal. Default = 0.00000001.
p_logging – Log level (see constants of class Log). Default = Log.C_LOG_ALL.
- C_TYPE = 'Model Predictive Control'
- execute(**p_kwargs)