simplifying crowd automation in the virtual laboratory of archaeology

SIMPLIFYING CROWD AUTOMATION IN THE

VIRTUAL LABORATORY OF ARCHAEOLOGY

Luís Miguel Sequeira,Leonel Caseiro Morgado, Eduardo Solteiro Pires

November 22

Virtual Archaeology

Using computer models for visualising cultural artifacts and heritage sites

Recent work also include crowd simulation (no more empty sites!) Example: Uruk in SL

Recent: Formulate hypothesis and test them on a virtual lab of archaeology

Lisbon 1755Project started informally in 2005, formally around 2007

Goal: depict the city of Lisbon that was destroyed by an earthquake on Nov 1st, 1755

Visitors will be able to attend special events and interact with inhabitants (AI-driven intelligent agents)

http://lisbon-pre-1755-earthquake.org/

Historians FTW!

Early attempts at virtual archaeology: showing off technology, historians/archaeologists only as consultants... at the end of the project

Today: Methodologies like the London Charter put the teams under supervision of a historian

Result: scientific accuracy

Virtual worlds

No need for separate modelling/rendering pipeline (when using prims)

No need to develop the engine

Historians can also formulate hypothesis and move objects around without the need to talk to the technical team!

Make it simple!

But what about crowd simulation?

Crowd simulation is not new...

Virtual worlds are not new...

Intelligent agents are not new...

... all, however, require programmers to implement simulation parameters!

How can historians do that?

Typical simulations

How did people use the spaces?

Can we recreate events in a convincing way using AI?

Can we see emergent behaviour (peasants avoiding to bump into nobles, or seeking priests for a blessing?)

Agents interacting with human visitors

The concept (1)

Classical model with perception/selection/behaviour modules

Movement is towards attractors/getting away from repellers (e.g. other agents) — typical from swarms

Agents pick up their own rules for better achieving their goals using genetic algorithms (GA)

The concept (2)

For the GA, the fitness function depends on the length of the longest, unimpeded line of sight (as calculated by the ray-casting functions in LSL) and the nearness of the current goal

All parts of the simulation engine use “standard” algorithms; further research could explore alternatives

What’s new?

It’s cruel to expect historians to learn about programming AIs...

Instead, we borrow ideas from games: agents have goals which are represented by cubes on the terrain

So to “programme” a goal, a historian just drops a cube on the ground. Simple!

Defining goalsEnergy level: Moving around reduces energy; goal is to find inn to eat/home to sleep

Money level: Agents earn a daily wage (motivation to go to job area); working reduces energy level

Happiness level: Working is boring, so agents will look for entertainment areas

Interaction moduleNPC belong to a ‘class‘ — e.g. nobleman, priest, peasant, merchant, foreigner, beggar...

Matrix of interaction between each class (peasant bows before nobleman)

Very simple: friend/foe/neutral but this may be changed later

Friend/foe act as potential attractors/repellers too

Summarising...

To set goals, historians place cubes around the location, and adjust them in real-time

To define NPC/NPC interactions, historians assign NPC to classes on a web page (no programming)

Status & LimitationsPrototype is not yet functional

Suitable only for small crowds (too many cubes otherwise!)

Difficulties making it work across SL and OpenSim (original requirement)

User validation was not performed yet

Overall concept fits requirements as per interviews, but might not be suitable

Future workCubes attracting just one NPC (which sits on it)

Combine cubes (sitting on one activates another)

Interaction matrix: per NPC and dynamically adjusted

Autonomously-moving cubes?

Games? Other platforms?

Thank you for listening!

I welcome your feedback and comments!

lms@esoterica.pt