An agent receives inputs from its environment in the form of perceptions and it outputs things to its environment in the form of actions. Perceptions and actions are combined together in the perception action cycle. The perception action cycle is an inherently causal process as actions precede perceptions which may themselves be preceded by previous actions.
In stochastic systems it is especially important for agents to be able to perform causal reasoning so that they can determine what the most probable effects of their actions will be. The predicted outcomes of an action can be integrated into an agent's plans so that an agent can be prepared to deal with all contingencies.
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