What are the components of a Markov decision process (MDP)?Select one:a.States, actions, and rewardsb.States, outcomes, and rewardsc.States, actions, and costsd.States, outcomes, and costs

What is a state in a Markov decision process (MDP)?Select one:a.A possible outcome of an actionb.A representation of the current situationc.A representation of the future situationd.A representation of the past situation

What is a policy in a Markov decision process (MDP)?Select one:a.A set of rules for selecting actions and statesb.A set of rules for selecting actions in a given statec.A set of rules for selecting states in a given actiond.A set of rules for selecting outcomes

What is the goal of a Markov decision process (MDP)?Select one:a.To maximize the expected cumulative cost over a given time horizonb.To minimize the expected cumulative cost over a given time horizonc.To maximize the expected cumulative reward over a given time horizond.To minimize the expected cumulative reward over a given time horizon

What is the process of finding the optimal policy in a Markov decision process (MDP) called?Select one:a.Policy optimizationb.Markov optimizationc.Bellman optimizationd.Dynamic programming

What is the Bellman equation in a Markov decision process (MDP)?Select one:a.A recursive equation used to compute the transition probabilities of a stateb.A recursive equation used to compute the expected reward of a statec.A recursive equation used to compute the policy of a stated.A recursive equation used to compute the value function of a state