1. Giorgini - CoopIS 2001 Implicit Culture for Multi-agent Interaction Support Paolo Giorgini Department of Mathematics University of Trento pgiorgini@science.unitn.it Joint work with: Enrico Blanzieri, Paolo Massa and Sabrina Recla

2. Giorgini - CoopIS 2001 2 Outline Motivations Implicit Culture Systems for Implicit Culture Support (SICS) –A SICS for Multi-agent interaction support The eCulture Brokering System Conclusion and future work

3. Giorgini - CoopIS 2001 3 Motivations Interaction among agents is crucial for the efficiency of MAS –new agents enter into the system without the necessary knowledge and skills –new agents are not able to learn from the others’ behavior –it is not possible to define and represent a priori the relevant knowledge the agents need for the interaction

4. Giorgini - CoopIS 2001 4 Motivations In order to improve its behavior, a new agent should act consistently with the knowledge and the behaviors (culture) of the other agents. We propose a way for supporting multi-agent interaction based on the idea of Implicit Culture [ Blanzieri, Giorgini and Giunchiglia: 2000 ]

5. Giorgini - CoopIS 2001 5 Implicit Culture: basic definitions (1) Let P be a set of agents, O a set of objects, A a set of actions. We define: environment   P  O scene as the pair, where B  , and A  A situation as, where a  P and  is a scene executed situated action as the action executed in given situation. F  : deterministic function that describes the evolution of the environment.

6. Giorgini - CoopIS 2001 6 Environment a c b tt ”t”t ’t’t    FF 

7. Giorgini - CoopIS 2001 7 Environment a c b  t+1  ” t+1  ’ t+1 

8. Giorgini - CoopIS 2001 8 Implicit Culture: basic definitions (2) Random variable h a,t that describes the action that the agent a executes at the time t expected action as the expected value of h a,t, E( h a,t ) situated expected action as the expected value of h a,t given a situation ; E( h a,t | ) Cultural constraint theory for a group G  P, as a theory on the situated expected actions of the agents of G Cultural action w.r.t. G, as an executed action that satisfies a cultural constraint theory for G

9. Giorgini - CoopIS 2001 9 Implicit Culture: basic definitions (3) Implicit Culture Relation between G e G’ such that the expected situated actions of G’ are cultural action for G Implicit Culture phenomenon G and G’ are in implicit culture relation

10. Giorgini - CoopIS 2001 10 … the idea the agents of G’ perform actions that agents of G would perform in the same situations a tt  b  ’t  c  ”t  G’ G 

11. Giorgini - CoopIS 2001 11 Systems for Implicit Culture Support (SICS) Goal: establish an implicit culture phenomenon –acquisition of cultural constraint theory for G –proposing to G’ scenes such that the expected situated actions satisfy the cultural constraint theory for G.

12. Giorgini - CoopIS 2001 12 a tt  b  ’t  c  ”t  G’ G  SICS: architecture Observer DB Observer stores in a data base the situated executed actions of the agents of G.  Inductive Module  Inductive Module that using the data of the DB and the a priori theory  o, induces a cultural constraint theory  Composer Composer proposes to a group G’ a set of scenes such that the expected situated actions satisfies 

13. Giorgini - CoopIS 2001 13 a b c G’ G  SICS: architecture Observer DB Observer stores in a data base the situated execute actions of the agents of G.  Inductive Module  Inductive Module that using the data of the DB and the a priori theory  o, it induces a cultural constraint theory  Composer Composer proposes to a group G’ a set of scenes such that the expected situated actions satisfies   t+1  ’t+1  ”t+1

14. Giorgini - CoopIS 2001 14 The eCulture Brokering System The system is the result of collaboration between University of Trento and ITC-irst. GoalGoal: Permit to a citizen to access, via web, to the information about cultural goods collected in the (Trentino) museums. –The user demands the system information about cultural goods related to a particular epoch. –The system queries the databases of the museums and answers.

15. Giorgini - CoopIS 2001 15 Multi-agent Architecture Directory Facilitator (DF) knows the agents of the system and their services DF Agent Resource Broker (ARB) gives information about the external available resources ARB Broker (Br) builds an “answer” with some grade of specialization in an area. Br k Br 2 Br 1 … Wrapper (Wr) is the interface between the system and a database. DB Wr 1 Wr 2 DB Wr h … Personal Agent (PA) permits a user to access the system PA n PA 1 …

16. Giorgini - CoopIS 2001 16 User interface

17. Giorgini - CoopIS 2001 17 Agents interaction DF ARB Br k Br 2 Br 1 … DB Wr 1 Wr 2 DB Wr h … PA n PA 1 … 1) a user, by the PA, requests information about a century; the PA asks the DF which Broker can satisfy the request. 3) the Broker asks the ARB which are the external resources that can be useful. 2) The PA accepts or refuse the proposed Broker; it sends to the accepted Broker the request of the user. 4) The Broker asks the DF which Wrappers are able to interface the resources. 5) The Broker queries the Wrappers and build the answer for the user.

18. Giorgini - CoopIS 2001 18 Agents interaction DF ARB Br k Br 2 Br 1 … DB Wr 1 Wr 2 DB Wr h … PA n PA 1 … 1) a user, by the PA, requests information about a century; the PA asks the DF which Broker can satisfy the request. 3) the Broker asks the ARB which are the external resources that can be useful. 2) The PA accepts or refuse the proposed Broker; it sends to the accepted Broker the request of the user. 4) The Broker asks the DF which Wrappers are able to interface the resources. 5) The Broker queries the Wrappers and build the answer for the user. 6) The Broker send the answer to the PA that sends it to the user

19. Giorgini - CoopIS 2001 19 DF and Implicit Culture The DF provides a “yellow pages” service The Brokers are specialized in a different thematic areas The SICS is used to support the activity of the DF with the goal of suggesting to each PA the most suitable Broker

20. Giorgini - CoopIS 2001 20 DF and Implicit Culture Agents observed: Personal Agents (G = G’) Cultural Constraint Theory :  Proposed Scenes : Brokers Observed Actions: : The PA x request to the DF, at time t, a Broker for getting information about the century s : at time t, PA x accepts the Broker y, proposed by the DF, about the century s : at time t, PA x refuses the Broker y, proposed by the DF, about the century s

21. Giorgini - CoopIS 2001 21 Example Accept(VI)Refuse(IV) Br 3 Br 2 Br 1 Br 0 PA 0 Refuse(IV) PA 1 Refuse(XVI)Accept(VI)Refuse(IV) PA 2 Refuse(IV) PA 3 Accept(XVII) Accept(XI) Accept(II) Accept(XVII) Refuse(XVII) Observation stored by the SICS Accept(XVII)Accept(XIII) Accept(XI) PA 1 asks for a Broker for the VI century. 1) find the cultural actions Accepts(VI) 2) find the scenes 3. Propose the scene with the maximum probability of facilitation 1. Find the predictive agents 2. Select the similar agents PA 0, PA 2 PA 1 is more similar to PA 2 than to PA 0 Br 1

22. Giorgini - CoopIS 2001 22 The eCulture Brokering System Developed using JACK Intelligent Agents, a commercial agent-oriented development environment built on top of and fully integrated with Java It follows FIPA ( Foundation for Intelligent Physical Agents ) specifications for DF and ARB Databeses: Oracle and Microsoft Access

23. Giorgini - CoopIS 2001 23 Conclusions We have presented –the idea of Implicit Culture and how to use it for supporting Multi-agent interaction –eCulture Brokering System Implicit Culture Support allows us to improve the agents interaction without need to equip the agents with additional capabilities Future work: –Extend the use of SICS to other agents, in particular to the ARB (Agent Resource Broker) –Implementing the inductive module for inducing cultural constraint theories for different groups of agents

24. Giorgini - CoopIS 2001 24 … more http://www.science.unitn.it/~pgiorgio/ic