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Brussels 1 WP 1 Environment and Challenges Stephan Schuster University of Surrey Review Meeting Brussels, 31/10/2006
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31/10/2006 Review Meeting Brussels 2 WP 1 Objectives Build software environment Define and formalise suitable challenges Compare solutions found by agents to solutions found by human societies
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31/10/2006 Review Meeting Brussels 3 WP 1 Status Year 1Year 2Year 3 Environment Software first version First challenge implementations and final EM (D6) Comparison with human societies Challenge implementation (ongoing) Challenge definition (M1.1)
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31/10/2006 Review Meeting Brussels 4 Environment overview Specifies the composition of the world (plants, tokens etc.) and physical constraints of agents (e.g. agent lifespan, metabolism, mating rules) for a scenario Provides the actions agents can apply in this world (subject to the physical and logical constraints set out in the spec) Scenarios are generated from a scenario definition file
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31/10/2006 Review Meeting Brussels 5 Physics of the environment Environment Maximum number of agents (MaxPop) and plants (MaxPlants) Time steps per virtual day (T) Agents Maximum viewing (N) and hearing (H) distance Maturity age (AI), Maximum age (MaxAge) Pregnancy period (Mc), Energy share to child (Ms) Plants Energy increase per time step (Er) Time steps to grow (Tr) MA X 0 6 months12 months18 months AVERAGE PLANT ENERGY
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31/10/2006 Review Meeting Brussels 6 Challenges - Definition A challenge is a specific configuration of the environment. A challenge consists of Specification of a problem environment Translation of the problem into environmental constraints and distribution of objects Possible criteria for success
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31/10/2006 Review Meeting Brussels 7 Implementing/Formalising Challenges The challenge is to be defined by specifying mainly the geographical and physical features of the world Most scenarios are simple – based on food gathering (e.g. interim challenges, or Hunter- Gatherer Challenge from the Annex) So: The scenarios are described and generated by the spatial distribution of food
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31/10/2006 Review Meeting Brussels 8 Implementing/Formalising Challenges – ‘Scenario Files’ Modeller defines the location and distribution of objects (e.g. 100 agents with preferences for plant type x in region (0 0, 0 100, 100 100, 100 0) Detailed setup possible, but may result in repetitive information and large files
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31/10/2006 Review Meeting Brussels 9 Implementing/Formalising Challenges – ‘Scenario Generator’ Idea: Describe the world at an abstract level, let the software generate objects and geography matching the description For example: Uneven distributed patches of plants, long distances to travel, agents with different preferences … NTSG generates a world satisfying such kinds of constraints
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31/10/2006 Review Meeting Brussels 10 Software Architecture + implementation Agents EM NTVM Platform Postgres MapViewer NTSG
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31/10/2006 Review Meeting Brussels 11 Tools - NTSG
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31/10/2006 Review Meeting Brussels 12 Tools - MapViewer Visualisation Allows scrolling and zooming the whole landscape Uses Open-Source GIS software and a spatial postgres database Thin client accessible from any browser
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31/10/2006 Review Meeting Brussels 13 Tools – MapViewer
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31/10/2006 Review Meeting Brussels 14 Summary EM released First challenges implemented Software: NTSG, MapViewer
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