1. Intelligent Agents for norm-regulated MAS Alberto Sardinha Ricardo Gralhoz José Viterbo Karin Breitman

2. © LES/PUC-Rio Outline Introduction to Intelligent Agents – Alberto Sardinha Ontologies – Alberto Sardinha Conflict Resolution – Alberto Sardinha ‘Intelligent’ norm violation – Ricardo Gralhoz Policy-Based Context-Aware Applications for Mobile Computing – José Viterbo

3. Introduction to Intelligent Agents Alberto Sardinha

4. © LES/PUC-Rio Intelligent Agents Why should I use Intelligent Agents? –To solve complex problems –Dynamic and Nondeterministic environments –Learn automatically from experience –Open Systems SARDINHA, J.A.R.P. A Method and a Framework for Building Intelligent Agents. ScD Thesis, Dep. de Informática, PUC-Rio, 2005.

5. © LES/PUC-Rio Intelligent Agents Architectures RUSSELL, S.; NORVIG, P.. Artificial Intelligence. Prentice Hall, ISBN 0-13-103805-2, 1995.

6. © LES/PUC-Rio Intelligent Agents Architectures WOOLDRIDGE, M.. Intelligent Agents. G. Weiss (ed.), MULTIAGENT SYSTEMS: A MODERN APPROACH TO DISTRIBUTED ARTIFICIAL INTELLIGENCE.The MIT Press, Second printing, 2000.

7. © LES/PUC-Rio Intelligent Agents Architectures SARDINHA, J.; GARCIA, A.; MILIDIÚ, R.; LUCENA, C..The Agent Learning Pattern. SugarLoafPLoP'04, Fortaleza, Brazil, August 2004.

8. Ontologies for norm-regulated MAS Alberto Sardinha

9. © LES/PUC-Rio Ontologies and Intelligent Agents ANTONIOU, G.; HARMELEN, F.. A Semantic Web Primer MIT Press, ISBN 0-262-01210-3, 2004.

10. © LES/PUC-Rio Ontologies and Intelligent Agents Semantic Web Agents will make use of all these outlined technologies: –Metadata will be used to IDENTIFY and EXTRACT information from web sources –Ontologies will be used to assist in Web searches Interpret retrieved information Communicate with other agents –Logic will be used for processing retrieved information and drawing conclusions ANTONIOU, G.; HARMELEN, F.. A Semantic Web Primer MIT Press, ISBN 0-262-01210-3, 2004.

11. © LES/PUC-Rio Normative Ontologies Roles – a fundamental concept for open software systems Unknown entities increase the opportunity to happen unpredictable and non-desired situations Regulation over roles are needed! A generic ontology is presented to regulate agent actions –Uses NORMS to police agents’ actions FELICISSIMO, C.; LUCENA, C.; CARVALHO, G.; PAES, R.. Normative Ontologies to Define Regulations Over Roles in Open Multi-Agent Systems. In: AAAI Fall Symposium on Roles- an interdisciplinary perspective, 2005, Hyatt Crystal City in Arlington, Virginia.

12. © LES/PUC-Rio Normative Ontologies Norms can control the action performed in an open MAS defining which agents are: –PERMITTED –OBLIGATED –PROHIBITED An ontology can support norms regulation according to the Deontic Logic FELICISSIMO, C.; LUCENA, C.; CARVALHO, G.; PAES, R.. Normative Ontologies to Define Regulations Over Roles in Open Multi-Agent Systems. In: AAAI Fall Symposium on Roles- an interdisciplinary perspective, 2005, Hyatt Crystal City in Arlington, Virginia.

13. © LES/PUC-Rio Normative Ontologies FELICISSIMO, C.; LUCENA, C.; CARVALHO, G.; PAES, R.. Normative Ontologies to Define Regulations Over Roles in Open Multi-Agent Systems. In: AAAI Fall Symposium on Roles- an interdisciplinary perspective, 2005, Hyatt Crystal City in Arlington, Virginia.

14. © LES/PUC-Rio Normative Ontologies Presents case study of a Urban Traffic Simulator System (UTTS) Three agent roles: –Car Driver –Police Officer –Pedestrian FELICISSIMO, C.; LUCENA, C.; CARVALHO, G.; PAES, R.. Normative Ontologies to Define Regulations Over Roles in Open Multi-Agent Systems. In: AAAI Fall Symposium on Roles- an interdisciplinary perspective, 2005, Hyatt Crystal City in Arlington, Virginia.

15. © LES/PUC-Rio Normative Ontologies Ontology extension FELICISSIMO, C.; LUCENA, C.; CARVALHO, G.; PAES, R.. Normative Ontologies to Define Regulations Over Roles in Open Multi-Agent Systems. In: AAAI Fall Symposium on Roles- an interdisciplinary perspective, 2005, Hyatt Crystal City in Arlington, Virginia.

16. © LES/PUC-Rio Normative Ontologies Ontology Instantiation FELICISSIMO, C.; LUCENA, C.; CARVALHO, G.; PAES, R.. Normative Ontologies to Define Regulations Over Roles in Open Multi-Agent Systems. In: AAAI Fall Symposium on Roles- an interdisciplinary perspective, 2005, Hyatt Crystal City in Arlington, Virginia.

17. © LES/PUC-Rio Normative Ontologies Ontology Instantiation FELICISSIMO, C.; LUCENA, C.; CARVALHO, G.; PAES, R.. Normative Ontologies to Define Regulations Over Roles in Open Multi-Agent Systems. In: AAAI Fall Symposium on Roles- an interdisciplinary perspective, 2005, Hyatt Crystal City in Arlington, Virginia.

18. © LES/PUC-Rio Normative Ontologies - Conclusions Normative approach to define regulations over roles in open MAS. Provides a semantic support for agents –Reason about action selection More details on agent implementation is needed –Details on the logic? –What was used for processing retrieved information and drawing conclusions?

19. Conflict Resolution Alberto Sardinha

20. © LES/PUC-Rio Conflict Resolution Agent decision models are typically based on an attempt to: –Reach goals –Satisfy desires –Fulfill obligations –Etc The main problem is to resolve the conflicts among attitudes: –Which of the desires and obligations the agent will follow given his beliefs and intentions BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

21. © LES/PUC-Rio Conflict Resolution BOID (Beliefs-Obligations-Intentions-Desires) –Feed-back loops to consider all effects of actions –Mechanism to resolve conflicts between outputs of its four components Agent reasoning concepts are grounded into these four classes: –Beliefs are informational attitudes (How the world is expected to be) –Obligations and Desires are the external and internal motivational attitudes –Intentions are the results of decision making BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

22. © LES/PUC-Rio Conflict Resolution BDI + Obligations –Incorporate Obligations, Norms and Commitments of social agents and social rationality Presents 15 types of conflicts which can occur between these four concepts. Examples: –BO conflict: It is obligatory to see my mother-in-law this weekend But I think I have no time to go BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

23. © LES/PUC-Rio Conflict Resolution Example of conflict: –BOI conflict If I smoke, I should smoke in a smoking area I intend to smoke However, my office is a non-smoking area Agent types and conflict resolution –Order of overruling –Only considers the cases where the belief component overrules any motivational attitude component Instead of 24 cases, only 6 cases are left BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

24. © LES/PUC-Rio Conflict Resolution Agent types and conflict resolution –Realistic = the six conflict type where beliefs override all other components –Simple-minded (BIDO and BIOD) = prior intentions overrule desires and obligations –Selfish (BDIO and BDOI) = desires overrule obligations –Social (BIOD, BOID and BODI) = obligations overrule desires BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

25. © LES/PUC-Rio Conflict Resolution A set of observations W –Can not be overridden Initial sets of defeasible rules for the components: –B, O, I -, D An ordering function ρ to resolve conflicts –Define a function ρ on rules that represents the type of agents –In case of multiple applicable rules, the one with the lowest ρ value is applied –ρ is complete: it assigns a unique value to each rule BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

26. © LES/PUC-Rio Conflict Resolution BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

27. © LES/PUC-Rio Conflict Resolution

28. © LES/PUC-Rio Conflict Resolution BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

29. © LES/PUC-Rio Conflict Resolution BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

30. © LES/PUC-Rio Conflict Resolution Example 1: (BD conflict) –I would like to take a long vacation –I would need to get time off from work to take a long vacation –But I can´t get time off from work Prolog rules: –b_rule(ex1, true -> ~time_off). –b_rule(ex1, ~time_off -> ~vacation). –d_rule(ex1, true -> vacation). BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

31. © LES/PUC-Rio Conflict Resolution We first derive all beliefs resulting in the following extension: –[~time_off,~vacation] This extension is input to the desire component Because the only D-rule is not applicable, the final result remains the same: –[~time_off,~vacation] BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

32. © LES/PUC-Rio Conflict Resolution Example 2: (BOID conflict) –I intend to go to a conference –It is obligatory for me not to spend too much money for the conference –Either I should pay for a cheap flight ticket and stay in a better hotel, or I should pay for an expensive flight ticket and stay in a budget hotel –I desire to stay in a better hotel –But, I know that the secretary has booked an expensive flight ticket to me BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

33. © LES/PUC-Rio Conflict Resolution Prolog rules: –b_rule(ex2, true -> expensive_ticket). –b_rule(ex2, ~too_much_money -> ~cheap_hotel & ~expensive_ticket). –b_rule(ex2, ~too_much_money -> cheap_hotel & expensive_ticket). –i_rule(ex2, true -> conference). –o_rule(ex2, conference -> ~too_much_money). –d_rule(ex2, true -> ~cheap_hotel). BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

34. © LES/PUC-Rio Conflict Resolution Simple Minded agent of type ‘BIOD’ –First derive all beleifs and intentions –[conference, expensive_ticket] Because it is a social agent, the obligation rule is applied first –[~too_much_money,conference, expensive_ticket] The extension is FED BACK into the the B component where it trigger the third rule –[cheap_hotel,~too_much_money,conference, expensive_ticket] BROERSEN, J.; DASTANI, M.; HULSTIJN, J.; HUANG, Z.; TORRE, L van der. The BOID architecture: conflicts between beliefs, obligations, intentions and desires. International Conference on Autonomous Agents, 2001.

35. © LES/PUC-Rio Conclusions Resolve conflicts among informational and motivational attitudes The order of the derivations determines the type of an agent An important ingredient in the BOID architecture is the presence of feedback loops