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Agent-based Decision Support Challenges for co-ordination and communication

Agent-based Decision Support Challenges for co-ordination and communication. Sascha Ossowski Artificial Intelligence Group Dpt. of Informatics, Statistics and Telematics School of Engineering University Rey Juan Carlos. Agent-based Decision Support. 1. The Decision Support Problem

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Agent-based Decision Support Challenges for co-ordination and communication

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  1. Agent-based Decision SupportChallenges for co-ordination and communication Sascha Ossowski Artificial Intelligence Group Dpt. of Informatics, Statistics and Telematics School of Engineering University Rey Juan Carlos Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  2. Agent-based Decision Support 1. The Decision Support Problem 2. Co-ordination issues in DS 3. Communication issues in DS 4. Conclusions Outline: Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  3. Decision Support Systems Decision Support System: • Information system that helps preparing a decision by providing decision-relevant data • but also assists the decision-maker in exploring its meaning Example: Road Traffic Management • urban motorway network • Traffic Control Centre (TCC) is to assure a smooth flow of vehicles • assist TCC engineers in their decision-making respecting coherent signal plans Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  4. Incidents Bus fleet monitoring system Operator support system GPS Control actions Example: Bus Fleet Management • Some incidents: • individual/generalised delays • delays in several lines • vehicle malfunctions • . . . • Some control actions: • detour • limitation of the service • frequency regulation • . . . Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  5. Example: Emergency Management What may happen? (considering that no control action is taken) Overflowing incidents in the Cullera and Sueca sections. Blocked road sections: C-335 between Guadamar and Alginet What may happen if the opening degrees of the reservoir’s floodgates are modified? Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  6. I -I would like to buy 100 shares of Terra B-Be careful, this is a risky order I - Can you explain why? B - Because this stock has a high volatility and, as far as I know, your risk aversion is high I -Which is the volatility value? B - 40% I -Forget the initial order. I will buy 75 shares of stock A Information Assistance Proactive Tutoring B -The order has been executed Automatic Advice Example: eMarkets Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  7. Agent-based Decision Support 1. The Decision Support Problem 2. Co-ordination issues in DS 3. Communication issues in DS 4. Conclusions Outline: Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  8. Services in DS domains Services: • Domain services(Ontology, Data, …) • Basic DS services: • DS Ontology • Alarms (problem identification) • Diagnosis (causes) • Repair (action plan generation) • Simulation (explore potential effects) • Composite DS services (DS questions, …) Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  9. Example: Domain service Road Traffic Management: Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  10. Example: Ontology Road Traffic Management: • nodes • sections • connections • measurement points • control devices • routes • . . . Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  11. Example: Basic DS services Road Traffic Management: Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  12. Example: Basic DS services Bus fleet management: (defrule Generalised_Delay (bus (id ?b1) (delay ?m1) (line ?l)) (bus (id ?b2) (delay ?m2) (line ?l)) (test (neq ?b1 ?b2)) (test (> ?m1 0)) (test (> ?m2 0)) => (assert (generalised_delay ?l)) ) (defrule Individual_Delay_Low (bus (id ?b) (delay ?m) (line ?l)) (test (> ?m 0)) (test (< ?m 5)) => (assert (individual_delay (bus ?b) (severity low))) ) Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  13. Co-ordination of DS services DS service composition: • Understand the current situation: • “What is happening in S ?”: problem identification + diagnosis • “What to do on D in S ?”: action planning + prediction • “Why is it happening”: explanatory facilities • Understand potential future situations: • “What may happen if E in S ?”: prediction + problem ident. + diagnosis • “What to do if E in S ?”: prediction + problem ident. + diagnosis + planning Challenge: Open service environments Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  14. Agent co-ordination (SE) • DS with multiple agents: • Traffic & emergency management: one agent per problem area • Bus fleet management: one agent per line • . . . • Co-ordination in agent society: • Subjective co-ordination (agent’s perspective): self-interested action • Objective co-ordination (designer’s perspective): normative biasing Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  15. Subjective co-ordination: model the outcome of self-interested interaction within bargaining theory Objective co-ordination: bias fallback position by issuing prescriptions Challenge: scalability Example: subjective and objective co-ordination Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  16. Agent co-ordination (DM) Groups of decision-makers: • Partially co-operative setting: • Several operators for different problem areas, bus lines etc. • Several entities affected by emergencies • Different levels of co-ordination services • Communication • Matchmaking support • Co-ordination decision-making support Challenges: Open environments + Mobility Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  17. Agent-based Decision Support 1. The Decision Support Problem 2. Co-ordination issues in DS 3. Communication issues in DS 4. Conclusions Outline: Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  18. Stock trading Financial Advice Fin. Info exchange Stock trading DS dialogues • Goal: expressive, flexible and structured DS dialogues • Principled extension of a core (standard) ACL I- I would like to buy 100 shares of Terra B- Be careful, this is a risky order I- Can you explain why? B- Because this stock has a high volatility and, as far as I know, your risk aversion is high I- Which is the volatility value? B- 40% I- Forget the initial order. I will buy 75 shares of stock A B- The order has been executed Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  19. DS Interactions and Organisational Roles: Example Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  20. request I- I would like to buy 100 shares of Terra warn B- Be careful, this is a risky order ask I- Can you explain why? B- Because this stock has a high volatility and, as far as I know, your risk aversion is high explain-why query I- Which is the volatility value? B- 40% inform I- Forget the initial order. I will buy 75 shares of stock A B- The order has been executed cancel / request acknowledge Formalising DS Speech Acts • Wierzbicka (1987): Catalogue of English Speech Act Verbs • more than 150 English CAs formalised in Natural Semantic Metalanguage (NSM) • Warn CA • I think Y will be done • I think of X as something that could be bad for you • I think X could be caused by Y • I say: X could be caused by Y • I say this because I want to cause you to know that X could happen Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  21. Extending the Role Model • Reuse of FIPA primitives based on their generic roles • Structured extensions through new (generic) roles Challenge: Structured library of reusable extensions to standard ACLs Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  22. Agent-based Decision Support 1. The Decision Support Problem 2. Co-ordination issues in DS 3. Communication issues in DS 4. Conclusions Outline: Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  23. Conclusions • Agent-based decision support: • added value in many MAS domains • research in co-ordination / communication • Communication: • relevance of a social stance on ACLs (backed by Social Theory) • link between organisational structure and ACL structure (AOSE, E-Institutions) • Co-ordination: • service co-ordination in open environments • co-ordination as a service: SE and DM perspectives Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

  24. Agent-based Decision SupportChallenges for co-ordination and communication Sascha Ossowski Artificial Intelligence Group Dpt. of Informatics, Statistics and Telematics School of Engineering University Rey Juan Carlos Sascha Ossowski / Artificial Intelligence Group sossowski@escet.urjc.es / http://www.ia.escet.urjc.es

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