6533b824fe1ef96bd12812bd

RESEARCH PRODUCT

MARL-Ped+Hitmap: Towards Improving Agent-Based Simulations with Distributed Arrays

Francisco Martinez-gilArturo Gonzalez-escribanoJuan M. OrduñaEduardo Rodriguez-gutiez

subject

020203 distributed computingComputer scienceDistributed computingMessage passing0202 electrical engineering electronic engineering information engineeringProcess (computing)Reinforcement learning020207 software engineering02 engineering and technologyCrowd simulationGranularityPartition (database)

description

Multi-agent systems allow the modelling of complex, heterogeneous, and distributed systems in a realistic way. MARL-Ped is a multi-agent system tool, based on the MPI standard, for the simulation of different scenarios of pedestrians who autonomously learn the best behavior by Reinforcement Learning. MARL-Ped uses one MPI process for each agent by design, with a fixed fine-grain granularity. This requirement limits the performance of the simulations for a restricted number of processors that is lesser than the number of agents. On the other hand, Hitmap is a library to ease the programming of parallel applications based on distributed arrays. It includes abstractions for the automatic partition and mapping of arrays at runtime with arbitrary granularity, as well as functionalities to build flexible communication patterns that transparently adapt to the data partitions.

yearjournalcountryeditionlanguage
2016-01-01
https://doi.org/10.1007/978-3-319-49956-7_17