GP Generation of Pedestrian Behavioral Rules in an Evacuation Model Based on SCA

Authors:
Stefania Bandini;Sara Manzoni;Giancarlo Mauri;Stefano Redaelli;Leonardo Vanneschi
Affiliations:
Complex Systems and Artificial Intelligence Research Center, University of Milan---Bicocca, Italy;Complex Systems and Artificial Intelligence Research Center, University of Milan---Bicocca, Italy;Complex Systems and Artificial Intelligence Research Center, University of Milan---Bicocca, Italy;Complex Systems and Artificial Intelligence Research Center, University of Milan---Bicocca, Italy;Complex Systems and Artificial Intelligence Research Center, University of Milan---Bicocca, Italy
Venue:
ACRI '08 Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry
Year:
2008

Citing 10
Cited 1

Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Genetic programming (videotape): the movie

Genetic programming (videotape): the movie
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Modelling Heterogeneity in Multi Agent Systems

EurAsia-ICT '02 Proceedings of the First EurAsian Conference on Information and Communication Technology
A Multi-Agent Cellular Automata System for Visualising Simulated Pedestrian Activity

Proceedings of the Fourth International Conference on Cellular Automata for Research and Industry: Theoretical and Practical Issues on Cellular Automata
Enhancing Cellular Spaces by Multilayered Multi Agent Situated Systems

ACRI '01 Proceedings of the 5th International Conference on Cellular Automata for Research and Industry
CA Approach to Collective Phenomena in Pedestrian Dynamics

ACRI '01 Proceedings of the 5th International Conference on Cellular Automata for Research and Industry
L*MASS: A Language for Situated Multi-agent Systems

AI*IA 01 Proceedings of the 7th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
The f.a.s.t.-model

ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
Towards a methodology for situated cellular agent based crowd simulations

ESAW'05 Proceedings of the 6th international conference on Engineering Societies in the Agents World

Generating inspiration for agent design by reinforcement learning

Information and Software Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a research in the context of pedestrian dynamics according to Situated Cellular Agent (SCA), a Multi-Agent Systems approach whose roots are on Cellular Automata (CA). The aim of this work is to apply Genetic Programming (GP) approach, a well known Machine Learning method belonging to the family of Evolutionary Algorithms, to generate suitable behavioral rules for pedestrians in an evacuation scenario. The main contribution of this work is in the design of a testset of GP generated behaviors to represent basic behavioral models of evacuees populating a only locally known environment, a typical scenario for CA-based models.