introduction of workpackage 2 - policy modelling

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FUTURE POLICY MODELLING (FUPOL)

WP2 – Policy Modelling


The main objective is to derive guidelines and a repository of generic causal modeling platform suitable for the spiral policy modelling approach consisting of:

• Cognitive Models: • Causal Models specified in Coloured Petri Net Formalism• Agent Behaviour

The scope of the models will be limited to the major domains in urban policies including: Land use and urban planning, Environment, Education, Demography, Finance, Economic Affairs, Family , Public Transport , Cultural Affairs, Social Affairs, Public Health and Hospitals.

Objectives


A specific objective is to develop theoretical models for the policy areas of the pilots to evaluate the applicability of the generic models in practice.

Some domains that have been identified are Land use and urban planning Sustainable development and environment Urban segregation and migration Education Demography

Objectives


Description of Work

In the social context, there is a lack of decision support tools that could help to deal with the design of a trade-off policy through a collaborative decision making approach in which citizen behaviour could be used to understand not only the acceptability of a certain policy, but also the dynamics of their shortages:

Why hidden shortages can emerge? How the policy handicaps will affect the communities? When deficiencies of a policy will be evident?

The causal modelling approach to be developed in this WP will contribute to understand the different relationships between citizens, community leaders, and government agents roles and to analyze through the simulation software to be developed in WP-4 the different consequences (both positives and negatives) of the different policies.


Description of Work

FCM: parameterize individual interactions as feedback loops

CPN: specification of emotion models based in affective science, in view of their large-scale causes and effects both for the individual agent and the multi-agent.


Tasks (1)

Task 2.1: Definition and Modelling of Requirements

This task seeks to develop a platform, method, and service for integrating expert knowledge and information from different domains to support policy decision making.

The Modelling requirements concerns how to develop accurate social and behavioural models and integrate them with engineering models (systems dynamic) to understand how consequences of government actions are propagated, in order to foster, encourage and facilitate collaboration between the citizens and government agents in order to improve policies effectiveness.


Tasks (2)

Task 2.2: Cognitive Modelling

FCMs are fuzzy-graph structures that provide an expressive and flexible method of capturing and representing complex relationships in an intuitive manner. FCMs have been successfully used to model complex systems in a variety of scientific areas.

In this task FCM models of specific policy domain will be implemented and evaluated with regard to other modelling approaches.


Tasks (3)

Task 2.3: Causal Modelling

Policy decisions and the propagation of its consequences is considered nowadays a complex problem. The use of CPN models will allow determining acceptable trade-off solution considering: citizen, community leaders and government agents.

Causal CPN models will be extended as agent-oriented Coloured Petri Nets with some intelligent elements, such as Goal, Knowledge, Environment, Make-decision and Sensor. CPN causal models will be autonomous agents and goal-driven.


Tasks (3)


Tasks (4)

Task 2.4: Model Parameterization

Scenario planning will be considered as a framework of support for decision-makings based on clarifyingcause-effect factors with respect to different boundary conditions and different citizens-stakeholders involvement in the decision making activity through social networks.

In this task, the weak and tight links generated from the FCM specifications will be weighted in the CPN model to determine the sensitivity of the social context to policy impacts in the quality factors perceived by the citizens and the stakeholders.


Tasks (5)

Task 2.5: Model Validation and VerificationState Space (SS) Analysis is a rigorous approach that can be supported by causal models developed under Coloured Timed Petri Net formalism.

Pattern recognition techniques will be applied to understand the main cause-effect relationships that can be generated by the model and will be classified as strong or weak links.

This qualitative information will be validated and verified for the different policy domains by experts and considering also historical data.


Role of Partners

UAB: Will lead the policy modeling research by analyzing the policy landscape together with users in selected domains relevant to cities and municipalities and will develop generic policy models. Those will be the basis to develop computer simulation models. Interfusion: Will develop tasks including analysis of existing policy models, the construction of scenarios and model building, by means of Cognitive maps (CMs) and fuzzy cognitive maps (FCMs).PIN Scrl: Will contribute in the definition of the policy model to be exploited in the framework of the demonstrator implemented with the Municipality of Prato; RAU: Will be involved in the development of education-mobility-demographic models, but also in other policy models for describing in formal terms the comportment of these systems. The goal of these models will be to forecast how these linked systems will evolve over time, providing insights into the effects of policy changes;Zagreb City, Yorkshire, Prato, Pegeia and Yantai : Will provide input concerning user requirements, political process and priorities. Cellent and Qualysoft : will participate in the requirements collection phase to better understand user requirements.


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introduction of workpackage 2 - policy modelling

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