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A contracting model for flexible distributed scheduling
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AI
DOI：10.1007/BF02187332.png)
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Abstract
En 中文
We are interested in building systems of autonomous agents that can automate routine information processing activities in human organizations. Computational infrastructures for cooperative work should contain embedded agents for handling many routine tasks [9], but as the number of agents increases and the agents become geographically and/or conceptually dispersed, supervision of the agents will become increasingly problematic. We argue that agents should be provided with deep domain knowledge that allows them to make quantitatively justifiable decisions, rather than shallow models of users to mimic. In this paper, we use the application domain of distributed meeting scheduling to investigate how agents embodying deeper domain knowledge can choose among alternative strategies for searching their calendars in order to create flexible schedules within reasonable cost.
Keywords:
heuristics
meeting scheduling
contract net
search bias
cancellation
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