Chapman, J., Siebers, P.-O. and Robinson, D. orcid.org/0000-0001-7680-9795 (2017) Multi-agent stochastic simulation of occupants for building simulation. In: Barnaby, C.S. and Wetter, M., (eds.) Proceedings of the 15th IBPSA Conference. Building Simulation 2017, 07-09 Aug 2017, San Francisco, CA, USA. International Building Performance Simulation Association - IBPSA , pp. 179-188. ISBN 9781775052005
Abstract
This paper introduces a new general platform for the simulation of occupants’ presence and behaviours. Called No-MASS (Nottingham Multi-Agent Stochastic Simulation platform) the platform takes a selection of well validated stochastic models to generate a synthetic population of agents, predicts their presence and, in the case of residences also their activities and inferred locations, as well as their use of windows, lights and blinds. A social interaction framework is used to emulate negotiations amongst the members of diverse populations. Furthermore, machine learning techniques allow the agents to learn dynamic behaviours that maximise energy and/ or comfort rewards. This is complemented by a belief-desire-intent framework for the representation of less sophisticated behaviours for which data is scarce. Using the Functional Mockup Interface (FMI) co-simulation standard No-MASS is coupled with EnergyPlus: EnergyPlus parses environmental parameters to No-MASS which in turns parses back the energetic consequences of agents behaviours. Simulations demonstrating the range of results that No-MASS can produce are undertaken and presented.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2017 The Authors. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Architecture (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 22 Jun 2021 12:54 |
Last Modified: | 22 Jun 2021 12:54 |
Published Version: | http://www.ibpsa.org/?page_id=962 |
Status: | Published |
Publisher: | International Building Performance Simulation Association - IBPSA |
Refereed: | Yes |
Identification Number: | 10.26868/25222708.2017.051 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:175268 |