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

SO 3.2.2003Sascha Ossowski / Artificial Intelligence [email protected] / http://www.ia.escet.urjc.es

Agent-based Decision Support

Challenges for co-ordination and communication

Sascha Ossowski

Artificial Intelligence GroupDpt. of Informatics, Statistics and Telematics

School of EngineeringUniversity Rey Juan Carlos



1. The Decision Support Problem

2. Co-ordination issues in DS

3. Communication issues in DS

4. Conclusions

Outline:


Decision Support Systems

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

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: Bus Fleet Management

Some incidents: individual/generalised delays delays in several lines vehicle malfunctions . . .

Some control actions: detour limitation of the service frequency regulation. . .

Bus fleet monitoring

system

Operator support system

GPS

Incidents

Control actions


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?


Example: eMarkets

Automatic

Advice

Proactive

Tutoring

Information

Assistance

I I would like to buy 100 shares of Terra

I Forget the initial order. I will buy 75 shares of stock A

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%

B The order has been executed






4. Conclusions

Outline:


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, …)


Example: Domain service

low

SPEED (Km/h)

10 20 30 40 50 60 70 80 90 100 110 120 130

medium high

low

OCCUPANCY (Percentage)

10 20 30 40 50 60 70 80 90 100

medium high

low

SATURATION (Flow/Capacity)*100

10 20 30 40 50 60 70 80 90 100

medium high POS

1.0

1.0

POS

1.0

POS

Road Traffic Management:


Example: Ontology

COLLCEROLA

PORT VELL

TRINIDAD

Ring road from Trinidad to Collcerola

Ring road from Port Vell to Trinidad

T1

T2 T3

R

exit E1

exit E2

city centre A-19 from Mataró to Barcelona

P1

P2

P3

P4

P5

P6 P7 P8

BARCELONA MATARÓ


• nodes

• sections

• connections

• measurement points

• control devices

• routes

• . . .


Example: Basic DS services

Critical section: between Ronda de Dalt en Diagonal and Ronda de Dalt en d'Espluges

excess: 2200 veh/h paths:

From Collcerola to Llobregat -> [60, 80] % From Diagonal to Llobregat -> [20, 40] %

17PIV124PIV1

R1

13PIV2 8PIV1

Diagonal Can Caralleu

Congestion warning in Ronda de Dalt at Diagonal

State of control devices

Paths use

State of control zones

Incident congestion in the central lane at Diagonal

Section: Ronda de Dalt en Diagonal speed: low occupancy: high

Section: Ronda de Dalt en d'Esplugues speed: medium, high occupancy: low

Panel 17PIV1 : congestion at Diagonal



Regulator R1 : contention level medium

From Collcerola to Llobregat through Ronda de Dalt -> [40,60] %

From Collcerola to Llobregat through Can Caralleu -> [30,40] %

From Collcerola to Llobregat through alternative paths -> [10,20] %

From Collcerola to Can Caralleu : free

From Can Caralleu to Diagonal : with problems

From Diagonal to Llobregat : with problems



Example: Basic DS services

(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))))

Bus fleet management:


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


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


Example: subjective and objective co-ordination

• Subjective co-ordination:

– model the outcome of self-

interested interaction within

bargaining theory

• Objective co-ordination:

– bias fallback position by

issuing prescriptions

• Challenge: scalability


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






4. Conclusions

Outline:


Stock trading

Financial Advice

Fin. Info exchange

Stock trading

DS dialogues

I- I would like to buy 100 shares of Terra

I- Forget the initial order. I will buy 75 shares of stock A

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%

• Goal: expressive, flexible and structured DS dialogues

• Principled extension of a core (standard) ACL

B- The order has been executed


DS Interactions and Organisational Roles: Example

Financial AdvisoryInteraction

Financial InformationExchange

Stock Trading

Online Stock Broker

Financial Informee

Financial Informer

Financial Advisee

Financial Advisor

Investor

Stock Broker

Trader

<<plays>><<plays>>

<<plays>><<plays>> <<plays>>

<<plays>>


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 doneI think of X as something that could be bad for youI think X could be caused by YI say: X could be caused by YI say this because I want to cause you to know that X could happen

I- I would like to buy 100 shares of Terra

I- Forget the initial order. I will buy 75 shares of stock AB- The order has been executed

B- Be careful, this is a risky orderI- Can you explain why?B- Because this stock has a high volatility and,

as far as I know, your risk aversion is highI- Which is the volatility value?B- 40%

request warn

cancel / request

ask

explain-why

query inform

acknowledge


Extending the Role Model

• Reuse of FIPA primitives based on their generic roles

• Structured extensions through new (generic) roles

Online Stock Broker

Financial InformerFinancial Advisor Stock Broker

FIPA Requestee

FIPAInformer

ExplainerAdvisor

<<plays>>

<<plays>><<plays>> <<plays>>

Challenge: Structured library of reusable extensions to standard ACLs






4. Conclusions

Outline:


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



Challenges for co-ordination and communication

Sascha Ossowski

Artificial Intelligence GroupDpt. of Informatics, Statistics and Telematics

School of EngineeringUniversity Rey Juan Carlos

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

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