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IIIA - Artificial Intelligence Research Institute CSIC – Spanish Council for Scientific Research Deliverable 2.1: e-Institutions oriented to the use of.

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Presentation on theme: "IIIA - Artificial Intelligence Research Institute CSIC – Spanish Council for Scientific Research Deliverable 2.1: e-Institutions oriented to the use of."— Presentation transcript:

1 IIIA - Artificial Intelligence Research Institute CSIC – Spanish Council for Scientific Research Deliverable 2.1: e-Institutions oriented to the use of reputation Jordi Sabater-Mir Isaac Pinyol Daniel Villatoro Guifré Cuní Carles Sierra Juan Antonio Rodriguez Josep Lluís Arcos WP2 – Tools development

2 IIIA-CSIC Annex I: 1.Using the tool for e-institutions developed by partner number 4, study and design of the extra elements that are necessary to facilitate and study the use of reputation in an e-institution environment. 2.Development of an alpha version of the e-institution tool for reputation modelling. 3.Help to develop the applications allowing the different experiments described in the rest of workpackages to be run. Corresponding deliverables list: T0 + 12 (D2.1): e-Institutions oriented to the use of Reputation T0 + 20 (D2.2): e-Institution reputation software

3 E-Institutions IIIA-CSIC In human societies, institutions regulate the behaviour of people by enforcing laws, fixing protocols, etc. Open multiagent systems are populated by autonomous entities and therefore, there is no guarantee about what will be the behaviour of these entities. An e-institutions is the electronic equivalent of a traditional institution but for virtual environments.

4 E-Institutions IIIA-CSIC Some vocabulari: Role. Standardised patterns of behaviour required by all agents playing part in a given functional relationship. Dialogic Framework. Ontological elements and communication language (ACL) employed during an agent interaction. Scene. Agents meetings whose interaction is shaped by a well-defined protocol. Performative Structure. Complex activities specified as connections among scenes. Normative rules. Define the consequences of the agent actions within scenes.

5 E-Institutions IIIA-CSIC Performative structure Scenes Institutional agents

6 E-Institutions IIIA-CSIC governor

7 E-Institutions IIIA-CSIC

8 Using reputation in e-institutions IIIA-CSIC Integration of reputation mechanisms in the eI. Integration of a cognitive agent architecture in the context of an eI. Specification and implementation of a common ontology for reputation. Human interface with the eI.

9 IIIA-CSIC Integration of reputation mechanisms Centralized reputation (eBay, Sporas...) Distributed reputation (RepAge, ReGreT...) E-Institution Agent Governor Rep. system E-Institution Agent Governor Rep. system eI-service

10 Using reputation in e-institutions IIIA-CSIC Integration of reputation mechanisms in the eI. Integration of a cognitive agent architecture in the context of an eI. Specification and implementation of a common ontology for reputation. Human interface with the eI.

11 IIIA-CSIC EIAgent architecture

12 IIIA-CSIC EIAgent architecture

13 IIIA-CSIC Jadex architecture

14 IIIA-CSIC Jadex architecture

15 IIIA-CSIC Jadex architecture

16 IIIA-CSIC Jadex architecture

17 Using reputation in e-institutions IIIA-CSIC Integration of reputation mechanisms in the eI. Integration of a cognitive agent architecture in the context of an eI. Specification and implementation of a common ontology for reputation. Human interface with the eI.

18 CTR 1 CTR 2 CTR 3 OK! ??? ? ? ? The problem What if agents using different reputation models are in the same community? Different semantics, different representation of evaluations…. Pepe is Good? Pepe is 0.7? Pepe is 5? IIIA-CSIC

19 Let’s speak the same language! CTR 1 CTR 2 Ontology Mapping for CTR 1 Common Reputation Ontology Ontology Mapping for CTR 2 Communication IIIA-CSIC

20 The Ontology: Social Evaluation Evaluation Target Strength Value Context Source Entity Focus has belongs to Value [0,1]  R 0..1 1 1 1 belongs to Voice Eval. Gossiper Recipient belongs to has 0..1 has belongs to Norm Single Agent Group Institution is Skill Standard is IIIA-CSIC

21 The Ontology: Evaluative Belief Voice has belongs to 1 Eval. EvaluationEntity Entities has belongs to 1..n 1 Eval. Evaluation Entity EntitiesVoice IdTransEval. Real has belongs to 1 1..n 111 Reputation SharedImage ImageDExperienceSharedVoice EvalBelief SimpleBelief MetaBelief is IIIA-CSIC

22 Value Representation Evaluation Target Context Value Strength Source Entity Focus has belongs to [0,1]  R Value 0..1 1 1 1 belongs to Voice Eval. Gossiper Recipient belongs to has 0..1 has belongs to - Accuracy + Boolean False/True Discrete Sets {VB, B, N, G, VG} Probability Distribution Fuzzy Sets VBBNGVG 0 1 0.5 0 0 1 100755025 Value Bounded Real [0,1] IIIA-CSIC

23 Boolean {False,True} Discrete Sets {VB, B, N, G, VG} Probability Distribution VBBNGVG 0 1 0.5 Value Bounded Real [0,1] Max Min goodness FalseTrue Max Min goodness VBBNGVG Max Min goodness 0 1 0.5 BooleanDiscrete Set Bounded Real VBBNGVG 0 1 VBBNGVG 0 1 Prob. Distribution Min Max Semantic of the representations IIIA-CSIC

24 Conversions between types VBBNGVG Some of them… X ≥ 0.5 VG0.9 G0.7 N0.5 B0.3 VB0.1 [0.8,1)VG [0.6,0.8)G [0.4,0.6)N [0.2,0.4)B [0,0.2)VB Prob. Distribution Discrete Set {VB,B,N,G,VG} Real [0,1] Boolean {False,True} VBBNGVG VBBNGVGVBBNGVG falsetrue VBVG IIIA-CSIC

25 Conversion Uncertainty (CU) Uncertainty produced by conversion between representation types. To From BooleanDiscrete SetBounded RealProb. Dist. Boolean01.295.6421.19 Discrete Set004.3219.89 Bounded Real00015.55 Prob. Dist0000 CU values Let X,Y be representation types, then the CU value associated to the conversion from type X to Y is defined as: CU(X,Y) = H(Y | X) (Conditional entropy) IIIA-CSIC

26 Input calls Output calls directExp(DExperience) comm(EvalBelief) getReputation(Entity)  Reputation getReputation(Entity,Focus)  Reputation getImage(Entity,Focus)  Image API Interface Implementation(1) Decision Making Module Communication Module CTR y API y API interface and agent architecture IIIA-CSIC

27 Implementation(2) API interface for Abdul-Rahman & Hailes Model Distributed Model Agents evaluate direct experiences with {VU,U,T,VT} Agents can receive recommendations (direct experiences) from others. The model returns a degree of trust of agent A in context C with the values {Very Trustworthy, Trustworthy, Untrustworthy, Very Untrustworthy } or with an uncertain value: U +, U 0, U - (between VT-T, T-U, U-VU) Comm(DExperience) directExp(DExperience) getImage(Entity, Focus)  Image Evaluation: discrete sets {VB,B,G,VG} 1111111 VU UTVTU-U- U0U0 U+U+ Evaluation: probability distribution API Implementation IIIA-CSIC

28 Implementation(3) API interface for eBay Model Centralized Model Users evaluate their transactions sending to the system {+1,0,-1} The reputation of a concrete user is a number between 0 and 100.000, represented by a system of colored stars. API Implementation Comm(DExperience) getReputation(simpleAgent)  Reputation Evaluation: discrete sets VB 0N +1VG Evaluation: bounded real IIIA-CSIC

29 Using reputation in e-institutions IIIA-CSIC Integration of reputation mechanisms in the eI. Integration of a cognitive agent architecture in the context of an eI. Specification and implementation of a common ontology for reputation. Human interface with the eI.

30 IIIA-CSIC


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