Unsupervised Surrogate Agents and Search Bias Change in Flexible Distributed Scheduling
Sandip Sen, Edmund H. Durfee · 1995
Computational infrastructures for cooperative work should contain embedded agents for handling many routine tasks (Galegher, Kraut, & Egido 1990), 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 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. Introduction In characterizing computational tools for supporting cooperative work, researchers have often considered how dimensions of time and space lead to different tools. The result is often a characterization (Johansen 1988) of tools like that...