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Multi-agent stochastic simulation of occupants for building simulation

Chapman, Jacob; Siebers, Peer-Olaf; Robinson, Darren

Authors

Jacob Chapman

Darren Robinson



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.

Conference Name Building Simulation 2017, 15th IBPSA Conference
End Date Aug 9, 2017
Acceptance Date Apr 5, 2017
Publication Date Aug 7, 2017
Deposit Date Jan 5, 2018
Peer Reviewed Peer Reviewed
Keywords Multi-Agent Simulation; Occupant Behaviour Modelling; Built Environment; No-MASS
Public URL https://nottingham-repository.worktribe.com/output/876941
Publisher URL http://www.ibpsa.org/proceedings/BS2017/BS2017_051.pdf