Engineering Agent Systems for Decision Support Alberto Fernández School of Experimental Sciences and Technology University Rey Juan Carlos Madrid - Spain

Introduction Decision Support Systems Relevant in complex domains Intelligent DEcision-making Assistant (IDEA) Reactive: What is happening? Why is it happening? What can be done? What may happen if? Proactively: warnings Application of agent technology to design IDEAs

Analysis UER (User-Environment-Responsibility) technique User-centred Analysis use cases Environment-Centred Analysis reaction cases Responsibility-Centred Analysis goal cases

Task Design Tasks Questions A priori distribution Problem identification, Diagnosis, Action planning, Prediction Questions What is happening?: problem identification + diagnosis What to do?: action planning + prediction What may happen if?: prediction + p. identif.+ diagnosis What to do if?: predict. + identif. + diagnosis + planning A priori distribution physical, organisational, availability of knowledge, ... => multiagent system Interdependencies => co-ordination task

Method Design Tasks => Problem-Solving Methods Problem Identification classification method with two options: a) reference situation + difference classification b) direct classification Diagnosis: several methods a) classification method with additional information b) cover & differentiate method

Method Design Action Planning Prediction Co-ordination classification reasoning on predefined plans collection of plans to perform subtasks plan refinement strategy Prediction a) specific simulation methods b) a simplified model: envisionment graph simple systems, level of precision is not very high Co-ordination 1) dependency detection 2) option generation 3) management decision

An example: Road Traffic Management The domain: urban motorways Traffic Control Centre (TCC) is to assure a smooth flow of vehicles The task: assist TCC engineers in their decision-making respecting coherent signal plans Infrastructure (Barcelona): 52 VMS 3 groups of traffic lights 7 ramp access controls >300 sensors (loop detectors)

Traffic Management: Analysis

Traffic Management: Design Problem Identification and Diagnosis raw data pre-processing + fuzzy abstraction knowledge base of frames (problem scenarios)

Example scenario

Traffic Management: Design Problem Identification and Diagnosis raw data pre-processing + fuzzy abstraction knowledge base of frames (problem scenarios) Action Planning and Prediction calculation of contribution of each path to the problem coherent alternative signal plans are generated knowledge base of frames (traffic distribution scenarios)

Example scenario

Traffic Management: Design Co-ordination Centralised (TRYS) co-ordinator agent knowledge base of rules for managing dependencies Decentralised (TRYSA2) 11 autonomous traffic agents for managing problem areas knowledge base distributed among agents

Conclusions Agent-based approach can be applied to the construction of advanced DSS Agent-oriented knowledge and software engineering techniques can be applied Illustrated in the road traffic domain Improving integration of the different phases Currently, evaluation in traffic control (Basque Country) and bus fleet management (Southern Spain)

Engineering Agent Systems for Decision Support Alberto Fernández School of Experimental Sciences and Technology University Rey Juan Carlos Madrid - Spain