Intelligent agents are often described schematically as an abstract functional system similar to a computer program. Researchers such as consider goal-directed behavior to be the essence of intelligence; a normative agent can be labeled with a term borrowed from economics, "rational agent". In this rational-action paradigm, an IA possesses an internal "model" of its environment. This model encapsulates all the agent's beliefs about the world. The agent also has an "objective function" that encapsulates all the IA's goals. Such an agent is designed to create and execute whatever plan will, upon completion, maximize the expected value of the objective function. A reinforcement learning agent can have a "reward function" that allows the programmers to shape the IA's desired behavior, and an evolutionary algorithm's behavior is shaped by a "fitness function". Abstract descriptions of intelligent agents are sometimes called abstract intelligent agents (AIA) to distinguish them from their real world implementations as computer systems, biological systems, or organizations. Some autonomous intelligent agents are designed to function in the absence of human intervention. As intelligent agents become more popular, there are increasing legal risks involved.