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Artificial Intelligence and Proposal - Research Paper Example

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In the modern era of stringent global competition, businesses are finding it increasingly difficult to sustain their competitive advantages in the marketplaces. Off late business owners have realized the immense benefits of knowledge management practices to sustain competitive advantages and hence have invested in tools and techniques to capture, organize, disseminate and reuse knowledge related to their businesses…
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Artificial Intelligence and Proposal

Download file to see previous pages... [Liebowitz, J. 2001. p.1-6]
A research by Kaminka and Pynadath (2002. p.83-91) presented techniques of on-line monitoring of teams using a method of "overhearing" whereby their communication exchanges during business transactions are captured in computer systems and the learning of the agents are captured under three categories - No Learning, On-Line Learning and Using Previously Learned Predictions. They called the system as "Overseer" that can be effectively used to compare the performance gaps between novice agents and expert agents. The system could be used for performance evaluations of individuals as well as groups carrying out business transactions in any domain of the world. The researchers deployed two different hierarchies in the system - A team hierarchy and a plan hierarchy. The team hierarchy comprises of people fitting into the roles required to deliver tasks defined in the plan hierarchy. Hence, every individual in a role is expected to "execute a plan". They modeled the ground operations of an international airport whereby the human agents were allowed to query about the status of a plan and the future course of the plan in progress thus dealing with obstacles coming on the way of a plan. They querying was normally carried out by people in higher hierarchies and the plan reporting carried out by people in lower hierarchies. The learning about steps taken for plan executions were recorded in a plan library. They developed a probabilistic model of quantitative evaluation of the plan by plotting a time series of the plan state variables whereby all plans are represented by a set of Boolean random variables in such a way that the variable is true only if an agent is able to execute it at time "t". Thereafter the performance "belief" about an agent was plotted as a probability distribution with Markov property over all the variables within the set and was termed as Dynamic Belief Network (DBN). The start of a plan is overheard through initiation messages by the reporter and termination of plan overheard through ...Download file to see next pagesRead More
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