Control as Inference and Active Inference › Key Parameters

The key parameters for planning as message passing are:

• GAMMA: Discount factor multiplying future soft values during iteration. Values closer to 1 weight eventual docking more heavily against accumulated step costs, stretching the corridor of viable routes outward; smaller values myopically favor early escape from step costs and can shorten imagined plans accordingly.
• beta: Temperature dividing rewards inside the soft Bellman backup; $1/\beta$ is the inverse temperature. Small values sharpen optimality evidence toward the deterministic plan, while large values soften the posterior toward exploration.
• SLIP: Probability that the commanded move is replaced by a uniformly sampled direction, including the commanded direction itself. Raising it thickens the interior wall buffers of the value field and, at fixed $\beta$, shifts more posterior mass toward wall-adjacent routes where outward replacements are partially neutralized by boundary clamping.
• STEP_COST, GOAL_REWARD: Per-timestep cost and docking bonus that define the reward signal converted into optimality evidence. Their magnitudes relative to $\beta$, together with $\gamma$ and the horizon, set the effective urgency of arrival. Scaling every reward by $c$ while also scaling the temperature by $c$ leaves $r/\beta$ unchanged, so only reward-to-temperature ratios are policy-relevant under this parameterization.
• max_iter: Cap on fixed-point iterations, paired with a relative stopping tolerance of delta < 1e-7 scaled by the value magnitude. Convergence is geometric thanks to the contraction property shared with the hard Bellman operator, so the cap rarely binds on problems of this size.
• n_ep, max_steps: Number of sampled rollouts per temperature (400) and the per-rollout horizon cap (140 steps) used to estimate route density and mean return. The horizon cap bounds runtime but truncates episodes that never reach the dock. Because diffuse high-$\beta$ policies wander longer, they are the most exposed to truncation; increase the cap and rerun a sensitivity check before interpreting their occupancy fields or mean returns.