8. Strategic Reasoning and Adaptation in an Information Economy

1. 8. Strategic Reasoning and Adaptation in an Information Economy 96420-194 이승준

2. Introduction • UMDL(university of Michigan digital library) • Infrastructure should encourage • Flexibility • Extensibility • Scalability • Robustness

3. The Service Market Society (1/5) • Multi-agent information society • Collection interface agents(CIA) • Provide access and search services for collections of information • User interface agent(UIA) • Each user or library patron has a UIA which interacts with the UMDL to acquire services.

4. The Service Market Society (2/5) • Meditator agents • Transforms raw information resources into finished products • Query planning agents(QPAs) • Accept queries from users and return collections related to those queries • Auction agents • Matches UIA with an agent providing the service

5. The Service Market Society (3/5) • Facilitator agents • Facilitate the process of agents • Registry • To register unique agent-id • Service classifier agent(SCA) • Classify services by service description • Auction manager agent(AMA) • Returns a list of auctions which sell matching services

6. The Service Market Society (4/5)

7. The Service Market Socety (5/5) • The steps a service provider & a service consumer go through in SMS

8. The UMDL Ontology • Ontologies- to encode declarative descriptions of complex agent services. • Demands powerful expressiveness • Dynamic ontology

9. The UMDL Auction • Meditated(vs. Unmeditated) • Price(vs.Barter) • Formal(vs.Informal) • Parametrized auction descriptions

10. The Simple Market Scenario • 조건 • 각 agent들은 경쟁적으로 행동 • 가격을 주어진 대로 받아들임 • 공급자는 제시 가격이 가장 낮은 소비자 선택 • 제시 가격은 현재의 Load에 따라 증가 • 결과 • Decentalizied, Flexible resource allocation 수행 • Simple but Work well

11. Strategic Agents • 기대 이익을 최대화하도록 행동 • 독점시의 이익을 이용 • p-Strategy(Stochastic modelling based) • Markov Chains을 사용하여 상태 변화에 영향을 끼치는 인자를 찾아냄 • Number of buyers and sellers at the auction • Arrival rates of future buyers and sellers • Distribution of buy and sell prices

12. Strategic Agents-Experimental Results(1/4) • Experiment setting • C:competitive • P:p-Strategy • S-x:Seller X

13. Strategic Agents-Experimental Results(2/4) • Marginal profit of p-strategy(smart) agent decreases as the number of p-strategy agents increases.

14. Strategic Agents-Experimental Results(3/4) • Replacing Seller 1 with fixed-markup agent • Disadvantage of being less smart decreases as the number of smart agents increases.

15. Strategic Agents-Experimental Results(4/4) • Market efficency decreases with more p-strategy agents • But not decrease as sharply as one might expect

16. Learning Agents • Give sellers freedom to return services of any quility • Learn to avoid sellers that overchage • Provide a means for agents to discriminate between services • May learn from others’ interactions

17. Learning Agents-Experimental Results(1/3) • UIA: wants fast and cheap service. Willing to pay more for faster service. • QPA:Increase immediate profit(Failure means zero profit) • Different learning abilities • 0 Level: uses reinforcement learning on the prices/values received • 1 Level: try to model the other agents as 0-level agents

18. Learning Agents-Experimental Results(2/3) • 0-Level agents • Reachs equiblem price(marginal cost) • Robust

19. Learning Agents-Experimental Results (3/3) • 1-Level agents • Works good ifthere are no other 1-level agents • With other 1-level agents, performance on par with other 0-level agents

20. System-Wide Adaption • Price Monitor Agent • 가격이 Boundary를 벗어나면 agent 수 조절 • Auction Configuration • Create new auction at the request of agents

21. Price Monitor Agent • 가격에 따라 agent 생성/소거

22. Auction Configuration • Creates new auction at the requests

23. Conclusion • UMDL SMS는 desiderata를 잘 support • Can expanded more