Module markov_decision_process 

Markov Decision Process (MDP) solver.

Implements tabular MDP solving via Value Iteration, Policy Iteration, and Q-learning with full convergence tracking.

Example

use ipfrs_tensorlogic::markov_decision_process::{
    MarkovDecisionProcess, MdpStateId, MdpActionId, Transition, SolverConfig,
};

let mut mdp = MarkovDecisionProcess::new(3, 2);
mdp.set_terminal(MdpStateId(2), true).expect("example: should succeed in docs");
mdp.add_transition(
    MdpStateId(0),
    MdpActionId(0),
    Transition { to_state: MdpStateId(2), probability: 1.0, reward: 1.0 },
).expect("example: should succeed in docs");
let config = SolverConfig::default();
let (vf, result) = mdp.value_iteration(&config);
assert!(result.converged);
let _ = vf;

Re-exports

pub use functions::*;

pub use types::*;

Modules

functions

Auto-generated module

mdperror_traits

MdpError - Trait Implementations

solverconfig_traits

SolverConfig - Trait Implementations

types

Auto-generated module