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Intelligent Agents: Technology and Applications Unit Three: Tasks and Methods IST 597B Spring 2003 John Yen
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Relationship to Goals: How does a plan/process knowledge of an agent relate to its goals? Is a high-level task such as “Bring the pliers from the outhouse to the workshop” a goal? Is a desired state such as “my master needs pliers” a goal? Are these two goals the same or different?
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Two types of goals Goals to perform a high level task (Intent.To) Goals to achieve a desirable state (Intent.That) The two goals are often related. A high level task is often for achieving a desirable state (implicitly or explicitly in its effects). A desirable state can be achieved through a high- level task with matching effects. Example: Submit a paper vs having a paper published.
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Methods for an agent to accomplish desired goal states Find or synthesize a plan (from known actions) such that (1) the final state of the plan includes the desired goal, (2) the perquisite of the plan is met by the beginning state.
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Methods for an agent to accomplish Intent.To Decompose a high level task into lower level tasks/actions using plan/process knowledge of the agent. A lower level task in a plan may be further decomposed, resulted in a hierarchy.
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Be able to design cognitive agents that uses task decomposition to accomplish to-do goals. Be able to express multiple ways for an agent to accomplish a given task. Be able to understand how Taskable Agents achieve reactive planning. Learning Objectives:
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Primitive Action and Tasks A primitive action is an action that can be executed by an agent. A task is a higher-level action that can not be executed directly. A task needs to be decomposed into a process of primitive actions. A task can be viewed as a to-do goals.
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Example PickUp(object) is an action for Charley. Fetch(object, origin, destination) is a task for Charley. The process in HW1 decomposes the task Fetch into a sequence of four actions.
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Limitations of the HW1 Approach to Task Decomposition A task can be decomposed only in one way.
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A Better Task Decomposition Approach Allow a task to be decomposed in multiple ways, which we call methods. Each method is associated with a precondition, which describes the conditions required for the method to be applicable. Each method includes a process, which describes a set of actions / tasks that are connected to form a sequence, parallel branches, or other structures.
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Task Decomposition forms a Hierarchy Because a method may include a task, which is further decomposed by its own methods.
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By AirBy Car Fetch (o, from, to) Travel (from, to)
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Problem 1 (5%) Suppose Charley (the robot) needs to choose his means of transportation for moving from one location into another. That is, the action move(source, destination) is now replaced by a task Travel(source, destination). –Describe two methods for accomplishing this goal. –Describe the precondition of each method. –Describe the process of each method. You can use a diagram to describe the control flow between actions in the method.
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Method A: TravelByPlane Precondition: –There are airports in the source city and the destination city –The airports in the source and destination should be open Process –Buy Ticket –Go to departing airport –Board the airplane –Go to destination from the arrival airport
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Method B: Travel by Rental Car Precondition: –The agent has a rental car reservation –The agent can purchase required gas, and –Roads between the two locations are open Process –Go to rental car agency –Pick up the rental car –Select a route –Drive through the route
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Taskable Agents An agent architecture that supports tasks decomposition. Provides a language (TRL) for describing process knowledge for accomplishing tasks. Uses a Prolog-like inference engine (JARE) to describe states and inference rules regarding the world. Provides a control language.
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Problem 2: (5 %) Suppose Charley chose method A and start the trip with method A. Describe a situation that Charley needs to change from method A to method B after he starts executing plan A.
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