Within a logical$-$agent approach, agents almost never have access to the whole truth about their environment. Agents must therefore act under uncertainty. Identify the probable reason $/$ reasons of uncertainty.

A$.$ Incompleteness in the agent's understanding of the properties of the environment.

B$.$ Options, choices, and preferences of the properties of the environment.

C$.$ Use of formal language for representing and reasoning about the environment.

D$.$ Incorrectness in the agent's understanding of the properties of the environment.

Belief networks is a powerful tool for representing and reasoning with uncertain knowledge. It is a graph in which the following holds:

A$.$ A set of random variables makes up the nodes of the network.

B$.$ Some nodes have a conditional probability table that quantifies the effects that the parent nodes have on the node.

C$.$ It is a directed acyclic graph.

D$.$ A set of directed links or arrows connects pairs of nodes.

Modelling with Bayesian Networks require an assumption: There are no direct dependencies in the system being modelled which are not already explicitly shown via arcs. This is referred to as the

A$.$ Bayesian Dependency

B$.$ Markov Property

C$.$ Bayesian Property

D$.$ Arc Consistency