A Multiagent System Manages Collaboration in Emergent Processes

Publication Type:
Conference Proceeding
Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, 2005, pp. 175 - 182
Issue Date:
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Emergent processes are non-routine, collaborative business processes whose execution is guided by the knowledge that emerges during a process instance. In so far as the process goal gives direction to conventional business processes, the continually evolving process knowledge gives direction to emergent processes. Emergent processes may involve informal interaction, and so there is a limit to the extent to which the processes can be "managed". The collaboration however can be managed. Managing collaboration needs an intelligent agent that is guided not by a process goal, but by observing the performance of the other agents. Each agent has process knowledge --- that is information either generated by the individual users or is extracted from the environment, and performance knowledge --- that describes how the other agents, together with their 'owners', perform --- including how reliable they are. The integrity of the information derived from past observations decays in time, and so they have an inference mechanism that can cope with information of decaying integrity. An agent is described that achieves this by using ideas from information theory. The agents' internal representation language is probabilistic first-order logic. They derive models of the other agents using entropy-based inference that is based on random worlds. Maximum entropy inference is used to construct these models that are then refreshed as new information is received using minimum relative entropy inference.
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