2011
DOI: 10.1007/978-3-642-21940-5_6
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On the Benefits of Argumentation-Derived Evidence in Learning Policies

Abstract: An important and non-trivial factor for effectively developing and resourcing plans in a collaborative context is an understanding of the policy and resource availability constraints under which others operate. We present an efficient approach for identifying, learning and modeling the policies of others during collaborative problem solving activities. The mechanisms presented in this paper will enable agents to build more effective argumentation strategies by keeping track of who might have, and be willing to… Show more

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Cited by 3 publications
(1 citation statement)
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“…To achieve this, we need to identify agents whose policy constraints will most likely enable the execution of the delegated task. In our framework, whenever there is a task to be delegated, policy predictions are generated alongside the confidence of those predictions from the policy models that have been learned over time [6]. Confidence values of favourable policy predictions are compared to determine which candidate to approach for a resource, or to delegate a task.…”
Section: Task Delegation In Norm-governed Environmentsmentioning
confidence: 99%
“…To achieve this, we need to identify agents whose policy constraints will most likely enable the execution of the delegated task. In our framework, whenever there is a task to be delegated, policy predictions are generated alongside the confidence of those predictions from the policy models that have been learned over time [6]. Confidence values of favourable policy predictions are compared to determine which candidate to approach for a resource, or to delegate a task.…”
Section: Task Delegation In Norm-governed Environmentsmentioning
confidence: 99%