Modelling Dynamic Forgetting in Distributed Information Systems

Abstract. We describe and model a new aspect in the design of distributed information systems. We build upon a previously described problem on the microlevel, which asks how quickly agents should discount (forget) their experience: If they cherish their memories, they can build their reports on larger data sets; if they discount quickly, they can respond well to change in their environment. Here, we argue that on the macro-level, where agents disseminate information, the coordination of these micro-level strategies of discounting can have significant consequences on the system performance if the environment is uncertain. In our proposed model, a referral network disseminates information about a disruptive environment (a service provider) to a risk-averse client agent, who uses this information to maximise his profit and then gives feedback into the referral system. We model two simple strategies to dynamically find better discounting factors, through central and decentral control. We s...

• Type: Conference
• Year: 2010
• Where: KESAMSTA
• Authors: Nicolas Höning, Martijn C. Schut
• Keywords: Better Discounting Factors, Discounting, Intelligent Agents, KESAMSTA 2010, Referral Systems