Abstract

Agents in a network often face situations requiring them to make decisions without sufficient information. In such situations, they may postpone their decisions in order to observe and collect more information through learning from other agents. In this paper, we discuss the advantages of the postponement strategy from a game- theoretic perspective. We propose an extension to Chinese Restaurant Game, a general framework for social learning. In the proposed extension, rational agents may change their decision order at will. We find that two important elements in Chinese Restaurant Game, social learning and negative network externality, still dominate agents’ decision process and the postponement strategy. We study a two-player case in detail. Through simulations, we find that the signal quality and table size ratio greatly influence whether a rational agent will apply the postponement strategy or not. In some cases, rational agents may postpone their decisions in response to some, but not all, signals they received. We observe that such a strategy is informative, which also helps other agents improve their strategies accordingly.

Highlights

  • Rational agents in a social network may encounter incidents that require them to make decision without complete information

  • We demonstrate the critical influence on the decision order and how rational agents may choose when the order can be altered at will

  • We study the proposed two-player case through simulations

Read more

Summary

INTRODUCTION

Rational agents in a social network may encounter incidents that require them to make decision without complete information. In such occasions, they will learn the required knowledge from external information sources. We extend the legacy Chinese restaurant game to support the action of postponing, that is, agents or customers may postpone their decisions at will in exchange for collecting more informative signals. Such an extension significantly expands the degree of freedom of agent’s strategy and makes the model more suitable for real world applications. We discuss the influences through simulations, where we show how the table size and signal quality affect the final decision of each agent in the game

SYSTEM MODEL
EQUILIBRIUM ANALYSIS
Iterative Solution for Two-Player Case
SIMULATION RESULTS
CONCLUSION
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.