Question

In computer science, what does the Markov Property assume about future states?

• A. Future states depend on all previous states
• B. Future states depend only on the current state
• C. Future states depend only on the initial state
• D. Future states are completely random

Hint:

Markov Property → Future state depends only on the {current state} (memoryless system)

Answer 1

The Correct Option is B

Concept:
The Markov Property is a fundamental concept in probability theory and computer science, especially in models such as Markov Chains, Hidden Markov Models (HMM), and Markov Decision Processes (MDP). The Markov Property states that the probability of transitioning to the next state depends only on the current state, and not on the sequence of events that occurred before it.
Step 1:Understanding state transitions.
In many computational models, systems move between different states over time. These transitions can be represented probabilistically.
Step 2:Memoryless assumption.
The Markov Property introduces a memoryless assumption. This means the future state depends solely on the present state and ignores past states.
Step 3:Applications of the Markov Property.
This property is widely used in:

• Hidden Markov Models used in bioinformatics
• Speech recognition systems
• Natural language processing
• Reinforcement learning algorithms

Conclusion:
Thus, the Markov Property assumes that future states depend only on the current state and not on previous states.