Which of the following describes a difference between an MDP and a POMDP?

Question

BlackTom AI · Accepted Answer

First, let's restate what the question is asking: identify a difference between an MDP (Markov Decision Process) and a POMDP (Partially Observable Markov Decision Process).
Option: The state in an MDP is replaced with a belief state in a POMDP.
To evaluate this, consider how information is represented in each framework. In an MDP, the agent typically has full observability of the environment state, meaning the true state is known to the agent when making decisions. In a POMDP, the agent does not observe the true state directly; instead, it maintains a belief state, which is a probability distribution over possible states, updated as actions are taken and observations are received. This distinction is precisely what differentiates POMDPs from standard MDPs.
Now, what about potential counterpoints? Since the option states that the state in an MDP is replaced with a belief state in a POMDP, it accurately points to the core difference in information representation: full state knowledge vs. belief over states. It does not imply anything inaccurate about the MDP itself; it simply notes that POMDPs replace exact state knowledge with probabilistic beliefs.
If we imagine an alternative reading that “MDPs have no belief state,” that would be a mischaracterization because MDPs are defined by states being fully observed, not by the absence of belief reasoning per se. The belief state concept is introduced specifically to handle partial observability in POMDPs.
In summary, this option highlights a fundamental and canonical contrast between the two models: full observability in MDPs versus probabilistic belief over states in POMDPs. This makes the statement correct and central to understanding the difference between the two frameworks.

DD2380 HT24 (AIHT24_2) Q5: Decision making

Which of the following describes a difference between an MDP and a POMDP?

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