The correct answer is: Both Partial & Fully.
An observing environment is an environment that an agent can observe. In artificial intelligence, there are two types of observing environments: partial and fully observable environments.
In a partial observing environment, the agent can only observe a subset of the environment. This means that the agent does not have access to all of the information about the environment. For example, in a game of chess, the agent can only see the board and the pieces that are on it. It cannot see the opponent’s pieces or the opponent’s strategy.
In a fully observable environment, the agent can observe all of the information about the environment. This means that the agent has access to all of the state variables of the environment. For example, in a game of tic-tac-toe, the agent can see the entire board, including the opponent’s pieces and the opponent’s strategy.
Both partial and fully observable environments can be challenging for agents to learn and act in. In a partial observing environment, the agent must learn to deal with uncertainty. In a fully observable environment, the agent must learn to deal with a large amount of information.
The type of observing environment that is most appropriate for a particular problem depends on the problem itself and the resources that are available. For example, if the problem is very complex, it may be necessary to use a partial observing environment in order to reduce the amount of information that the agent must process.
Here are some additional details about each option:
- Option A: Partial observing environment. In a partial observing environment, the agent can only observe a subset of the environment. This means that the agent does not have access to all of the information about the environment. For example, in a game of chess, the agent can only see the board and the pieces that are on it. It cannot see the opponent’s pieces or the opponent’s strategy.
- Option B: Fully observable environment. In a fully observable environment, the agent can observe all of the information about the environment. This means that the agent has access to all of the state variables of the environment. For example, in a game of tic-tac-toe, the agent can see the entire board, including the opponent’s pieces and the opponent’s strategy.
- Option C: Learning environment. A learning environment is an environment in which the agent can learn from its experience. This means that the agent can improve its performance over time by observing the results of its actions.
- Option D: Both Partial & Fully. The correct answer is: Both Partial & Fully.