Adaptive Constraint-Based Agents in Artificial Environments

[AGENTS]   [Reactive Agents]   [Triggering Agents]   [Deliberative Agents]   [Hybrid Agents]   [Anytime Agents]

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Deliberative Agents

(Related publications: [PUBLink] [PUBLink])

Deliberative agents constitute a fundamentally different approach. The goals and a world model containing information about the application requirements and consequences of actions are represented explicitly. An internal refinement-based planning system (see section on [Planning]) uses the world model's information to build a plan that achieves the agent's goals. Planning systems are often identified with the agents themselves.

Deliberative agents have no problem attaining longer-term goals. Also, the encoding of all the special rules can be dispensed with because the planning system can establish goal-directed action plans on its own. When an agent is called to execute its next action, it applies an internal planning system:

IF (current_plan_is_not_applicable_anymore) THEN

Even unforeseen situations can be handled in an appropriate manner, general reasoning methods being applied. The problem with deliberative agents is their lack of speed. Every time the situation is different from that anticipated by the agent's planning process, the plan must be recomputed. Computing plans can be very time-consuming, and considering real-time requirements in a complex environment is mostly out of the question.

[AGENTS]   [Reactive Agents]   [Triggering Agents]   [Deliberative Agents]   [Hybrid Agents]   [Anytime Agents]

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Last update:
May 19, 2001 by Alexander Nareyek