banditpylib.learners.mab_collaborative_ftbai_learner

Classes

• MABCollaborativeFixedTimeBAILearner: Collaborative fixed-time learner aiming to identify the best arm in the

• LilUCBHeuristicCollaborative: Colaborative learner using lilucb heuristic as centralized policy

class banditpylib.learners.mab_collaborative_ftbai_learner.MABCollaborativeFixedTimeBAILearner(agent: banditpylib.learners.mab_collaborative_ftbai_learner.utils.MABCollaborativeFixedTimeBAIAgent, master: banditpylib.learners.mab_collaborative_ftbai_learner.utils.MABCollaborativeFixedTimeBAIMaster, num_agents: int, name: Optional[str] = None)

Collaborative fixed-time learner aiming to identify the best arm in the ordinary multi-armed bandit environment

Parameters

• agent (CollaborativeAgent) – one instance of an agent

• master (CollaboratveMaster) – instance of the master

• num_agents (int) – total number of agents involved

• name (Optional[str]) – alias name

Inheritance

property goal: banditpylib.learners.utils.Goal

Goal of the learner

property running_environment: Union[type, List[type]]

Type of bandit environment the learner plays with

class banditpylib.learners.mab_collaborative_ftbai_learner.LilUCBHeuristicCollaborative(num_agents: int, arm_num: int, rounds: int, horizon: int, name: Optional[str] = None)

Colaborative learner using lilucb heuristic as centralized policy

Parameters

• num_agents (int) – number of agents

• arm_num (int) – number of arms of the bandit

• rounds (int) – number of total rounds allowed

• horizon (int) – maximum number of pulls the agent can make (over all rounds combined)

• name (Optional[str]) – alias name

Inheritance