Framework for Integrated Simulations and Gaming

Transcription

1 Framework for Integrated Simulations and Gaming Jayanth Raghothama Gaming and Participatory Simulations Lab Division of Traffic and Logistics KTH, Royal Institute of Technology, Stockholm, Sweden

2 Simulation and Gaming Experi(m)ent(i)al, rule based, interactive environments where players learn by taking actions and experiencing the effects of their actions through feedback mechanisms Long history of being used for policy analysis and design Used for: Strategic Planning, learning and training, data collection, institutional analysis etc War Gaming, Business Simulations, City Planning, Emergency Management Best tool for studying complex systems, and testing policy options

3 Simulation and Gaming: Construction Games need to be fun, entertaining Games are safe, secure environments. Failure is acceptable and desirable First layer is interactive, gaming components based on game design and domain Second layer is a simulation: actions/parameters from players interaction fed into simulation Simulation provides feedback

4 Integrated Simulations: Motivation Many available simulators Operate on specific domains, or specific functions within one domain Complex problems require complex tools, complex simulations Infeasible to build complex simulations from scratch Organizational constraints Complex requirements Need ability to Bring together simulations from different domains Model and test larger and more complex scenarios Build complex simulations to study the joint effect of multiple phenomena: Emergent systems perspective

5 Architectures for Integrated Simulation: SIMNET, DIS and HLA SIMulator NETworking (SIMNET) to integrate combat simulators, used between 1983 and 1990 Distributed Interactive Simulations (DIS) to conduct real time war gaming. First DIS draft in 1990, still used today. Meant for war gaming High Level Architecture (HLA) developed for military purposes HLA is a general purpose architecture Allows for data communication and time synchronization

6 Limitations of Current Approaches, HLA Existing integrated platforms, expect all simulations to conform to a standard model Conforming to a standard model might not be possible Standard model might not be designed for new requirements Costly, time consuming, difficult to manage and scale HLA Lot of low level knowledge by practitioner Complex Semantic interoperability not possible

7 Architecture for Integrated Simulation and Gaming Goal: Develop a flexible, scalable, efficient architecture for gaming and integrated simulations Goal: Reusability, composability of components, models Generic gaming components for plug and play Supported by a federation of integrated simulations Simple architecture for integrated simulations Real data feeds Real time analytics, visualization GIS integration

8 GAMING & VISUALIZATION COMPONENTS UNITY3D, OTHER VISUALIZATION LIBRARIES Data/Control API Real Time Data/Control Flow Federation Simulation 1 Simulation 2 Simulation 3 Pub Sub Simulation 4 Simulation 5 Simulation 6 Mesoscopic Microscopic Institutio nal Structure Semantic Interoperability (Ontology/RDF) / Time Synchronization API Real Data / Simulated Data (Real Time/Big Data)

9 Challenges Semantic integrity, validity Data transformations has to preserve meaning and relationships of the data exchanged between simulators Time Synchronization Control of clocks needed Simulators are built to run as fast as possible Simulators need to be synchronized when events overlap. E.g: level crossin between a rail and road simulator Time synchronization between animation and federation Geometry, Geography Transformations

10 Use Cases(?) Response to big data by institutions Land Use + Traffic simulators Multi Modal Transport simulators Microscopic view of driver + Mesoscopic view of operators

11 Questions, Suggestions?