pomdp (version 1.2.4)

update_belief: Belief Update

Description

Update the belief given a taken action and observation.

Usage

update_belief(
  model,
  belief = NULL,
  action = NULL,
  observation = NULL,
  episode = 1,
  digits = 7,
  drop = TRUE
)

Value

returns the updated belief state as a named vector. If action or observations is a vector with multiple elements ot missing, then a matrix with all resulting belief states is returned.

Arguments

model

a POMDP object.

belief

the current belief state. Defaults to the start belief state specified in the model or "uniform".

action

the taken action. Can also be a vector of multiple actions or, if missing, then all actions are evaluated.

observation

the received observation. Can also be a vector of multiple observations or, if missing, then all observations are evaluated.

episode

Use transition and observation matrices for the given episode for time-dependent POMDPs (see POMDP).

digits

round decimals.

drop

logical; drop the result to a vector if only a single belief state is returned.

Author

Michael Hahsler

Details

Update the belief state \(b\) (belief) with an action \(a\) and observation \(o\) using the update \(b' \leftarrow \tau(b, a, o)\) defined so that

$$b'(s') = \eta O(o | s',a) \sum_{s \in S} T(s' | s,a) b(s)$$

where \(\eta = 1/ \sum_{s' \in S}[ O(o | s',a) \sum_{s \in S} T(s' | s,a) b(s)]\) normalizes the new belief state so the probabilities add up to one.

See Also

Other POMDP: MDP2POMDP, POMDP(), accessors, actions(), add_policy(), plot_belief_space(), projection(), reachable_and_absorbing, regret(), sample_belief_space(), simulate_POMDP(), solve_POMDP(), solve_SARSOP(), transition_graph(), value_function(), write_POMDP()

Examples

data(Tiger)

update_belief(c(.5,.5), model = Tiger)
update_belief(c(.5,.5), action = "listen", observation = "tiger-left", model = Tiger)
update_belief(c(.15,.85), action = "listen", observation = "tiger-right", model = Tiger)