Constraint Exploration and Envelope of Simulation Trajectories

TL;DR

This paper introduces a systematic methodology for exploring the 'envelope' of possible trajectories in simulations, using constraint-based search and modular rule compilation to understand emergent tendencies.

Contribution

It presents a novel approach combining constraint logic programming and modular rule compilation to efficiently explore simulation trajectory envelopes and identify emergent tendencies.

Findings

Method effectively explores simulation trajectory envelopes.

Constraint-based search identifies necessary tendencies.

Modular rule compilation improves exploration efficiency.

Abstract

The implicit theory that a simulation represents is precisely not in the individual choices but rather in the 'envelope' of possible trajectories - what is important is the shape of the whole envelope. Typically a huge amount of computation is required when experimenting with factors bearing on the dynamics of a simulation to tease out what affects the shape of this envelope. In this paper we present a methodology aimed at systematically exploring this envelope. We propose a method for searching for tendencies and proving their necessity relative to a range of parameterisations of the model and agents' choices, and to the logic of the simulation language. The exploration consists of a forward chaining generation of the trajectories associated to and constrained by such a range of parameterisations and choices. Additionally, we propose a computational procedure that helps implement this exploration by translating a Multi Agent System simulation into a constraint-based search over possible trajectories by 'compiling' the simulation rules into a more specific form, namely by partitioning the simulation rules using appropriate modularity in the simulation. An example of this procedure is exhibited. Keywords: Constraint Search, Constraint Logic Programming, Proof, Emergence, Tendencies