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BIHC Report Summary

Project ID: 655226
Funded under: H2020-EU.1.3.2.

Periodic Reporting for period 1 - BIHC (BIHC- Bio-inspired models of human crowds)

Reporting period: 2015-07-01 to 2016-12-31

Summary of the context and overall objectives of the project

With current consumer-grade personal computers, it is possible to display 3d virtual scenes with thousands of animated individual entities at interactive frame rates. Crowd simulations are, however, too often limited to characters lacking individuality and wandering in an environment without a specific goal. This situation is particularly problematic in the field of cultural heritage in real-time simulations of the past where the realism of individual behavior is critical. This proposal, through a collaboration across the computer science and the archaeology fields, seeks to address this problem. It aims at exploring bio-mimicking techniques in the development of a generative model for heterogeneity and spontaneity in behavioral animation of crowds. More specifically, the goals can be defined as (i) the development of a bio-inspired model of agency for virtual humans (which upgrades a previous prototype, part of my earlier research), (ii) the development of an authoring tool to interact with the parameters of that model and develop context-specific behaviors/animations, and finally (iii) the development of a proof-of-concept - the simulation of a historical environment, with the assistance of non-programmers using the authoring tool developed earlier.
This research aims to investigate crowds of virtual humans acting with realistic behavior at the individual level of simulation. The means to do such a study is through the exploration of animations of bio-mimicking techniques originating from ALife's framework and known as computational ecosystems. I want to develop a framework composed of a behavioral model (drawing on biological and economical tenets) and an associated authoring tool. The objective is to provide a software architecture for generative crowds and an associated application that enable users (non-programmers) to manipulate the parameters of the model, and consequently easily animate any historic/geographical scenario they may wish.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Performed study on the impact of biological inspired principles used in the simulation of groups and large populations. Results were reported publicly in the paper “Human Crowd Simulation: What Can We Learn From Alife?”, presented in the 15th International Conference on the Synthesis and Simulation of Living Systems (ALIFE XV).
Development of AI model, inspired by biological societies, for autonomous populations of virtual characters. Results and model were published in the paper “Bio-Inspired Virtual Populations: Adaptive Behavior with Affective Feedback.” in the 29th Conference on Computer Animation and Social Agents in Conference (CASA2016). An additional video documenting the main features of the model was produced.
Development of a first case study, the medieval village of Mértola, with integration of the AI model developed animating the population of virtual humans. The case-study took the form of a standalone application of the simulation of the village and it required a) interaction with Arqueologists from Campo Arqueologico de Mértola and b) coordination of work with Professors and Students from FCL, and c) art work on 3d models. The process of execution of the simulation was reported in the paper Virtual cities inhabited by autonomous characters: a pipeline for their production, presented at the 8th International Congress on Archaeology, Computer Graphics, Cultural Heritage and Innovation (Arqueologica 2.0).
Development of webpage ( and facebook page (, documenting and diffusing the project. These pages are publicly available, and contain relevant information about the project and associated documentation, reporting of events, images and videos of the simulations, etc.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The case study produced shows a population self-organized, expressing heterogeneous and spontaneous behaviors, with individual differentiation on emotional expression. These are promising results since, to our knowledge, and to date, there is no populations in cultural heritage simulations that raise the level of expressivity to such degree. By easing the usability of the model, and its expected wider acceptance and usage, the impact will be an increase on the number of simulations of ancient populations in historical reconstructions, nowadays typically void or not in real time.

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