Brussels 1 WP 1 Environment and Challenges Stephan Schuster University of Surrey Review Meeting Brussels, 31/10/2006

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

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)

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

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

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

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

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 0) Detailed setup possible, but may result in repetitive information and large files

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

31/10/2006 Review Meeting Brussels 10 Software Architecture + implementation Agents EM NTVM Platform Postgres MapViewer NTSG

31/10/2006 Review Meeting Brussels 11 Tools - NTSG

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

31/10/2006 Review Meeting Brussels 13 Tools – MapViewer

31/10/2006 Review Meeting Brussels 14 Summary EM released First challenges implemented Software: NTSG, MapViewer