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April 25, 2005
Expertise in context:Chapter 4: Experience and expertise: the role of memory in planning for opportunities
This chapter emphasizes the role of specific past experiences in memory that may form the basis of knowledge organization that differentiates experts from novices. Expertise in planning tasks is studied based on hypothesis that "expert planners are able to anticipate the circumstances related to satisfying goals, and therefore maximize their ability to respond to opportunities when they arise”. Three planning models are presented: AI model, Case-based planning model, Opportunism planning model.
AI model requires complete preplanning. Then the effect of the plan is projected on the world model to determine whether the outcome is successful before execution. The model requires the complete knowledge of the world and that the world model is stable. These requirements lead to costly information, complex planning, and lengthy execution time. In addition, many real world tasks require experts to work with uncertain and incomplete information. This model also cannot deal with multiple goals and postponed execution.
Case-based planning model - let past experiences tell the planner when and where plans work and do not work. Reuse past successful plan and avoid failed plan. "By experiencing failures and successes within a domain, expert planner is prepared to deal with future failure and opportunities when they occur. The framework of case-based planning modules that act to anticipate and avoid problems, repair faulty plan and store them. In this model, experts learn from failure by anticipating and avoiding them. However, it does not address the fact that expert also can predict and exploit opportunities as they arise.
Opportunism planning model: planner should be able to shift to a different strategy when notice opportunity even an unanticipated one.
• Demon model: Goals are characterized as agents having their own inferential power. A suspend goal continue to independently examine the ongoing input, realized satisfy condition and insert plan into current agenda. The reason for this model is there is no way to determine at the time of suspending goal in which condition the will be reactivated, and it is difficult to provide description of features that will be used to activate suspended goal.
The author argues that successful recognition of opportunities depend on feature use to index the suspended goal in memory. The model addresses the problem of how people recognize opportunities during plan execution. Power of opportunism rests in the abilities to reason at the time of goal suspension.
• Predictive encoding Model: Planners anticipate features in the world that indicate potential opportunities (condition that success execution should be possible), use features to index goal in memory. Activation of the features while pursue other goals will reactivate the suspended goal. The experience acquired in a domain allows experts to anticipate the circumstances that are related to opportunities to satisfy goal, and easily describe them in easily observable feature. The more one learn about the circumstances, the better one will be able to predict the feature and encode them.
The predictive encoding model is verified using “Trucker” computer simulation and an empirical study whose results support the model. Trucker involves receiving delivery requests, making decisions about which truck to assign a request, and which order parcels should be picked up. The empirical involves commonsense planning in a dorm room using college students as subjects. The results confirm that: 1) recognition is likely to occur based on features that could be anticipated from planning; 2) features associated with opportunities at the suspension time is more likely to lead to pending goal; 3) opportunities not anticipated may be missed; and features requiring inferential links to connect to goals is less likely to lead to recognition.
Posted by Sukanya at April 25, 2005 2:35 AM
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