pomdp_py.problems.tag.domain package¶

Submodules¶

pomdp_py.problems.tag.domain.action module¶

The Tag problem. Implemented according to the paper Anytime Point-Based Approximations for Large POMDPs.

Action space: The agent can take motion action and a tag action.

class pomdp_py.problems.tag.domain.action.TagAction[source]¶: Bases: Action

pomdp_py.problems.tag.domain.observation module¶

The Tag problem. Implemented according to the paper Anytime Point-Based Approximations for Large POMDPs.

Observation space: the agent observes the target’s location when the agent and: the target are in the same cell.

class pomdp_py.problems.tag.domain.observation.TagObservation(target_position)[source]¶: Bases: Observation

pomdp_py.problems.tag.domain.state module¶

The Tag problem. Implemented according to the paper Anytime Point-Based Approximations for Large POMDPs.

State space: state of the robot (x,y), state of the person (x,y), person found.

class pomdp_py.problems.tag.domain.state.TagState(robot_position, target_position, target_found)[source]¶: Bases: State

Module contents¶