Using the Instance-Based Learning Paradigm to Model Energy-Relevant Occupant Behaviors in Buildings

  • Jörn von GrabeEmail author


Human interactive behavior is accountable for most of the variance between the observed and predicted energy consumption of buildings, and is accordingly acknowledged as a major field of research into limiting building-related energy consumption. A thorough understanding of occupant behavior is critical to facilitate a more reliable prediction of energy consumption and identifying means by which pro-environmental behaviors can be promoted. Insights and models from psychology and sociology appear to be best suited to improving such understanding, and this article contributes to this end by developing and testing a cognitive model that serves as the core of a numerical human-building interaction model. The proposed implementation builds on instance-based learning, a well-established cognitive modeling paradigm, is integrated into a thermodynamic building model, and complemented by perception models for the approximation of the thermal and olfactory perception of the environment. The model successfully learns to interact plausibly with a set of elements of a model room—a heating system, a window, and the actor’s clothing—in order to establish predefined room conditions. Accumulation of context-specific instances in the declarative memory, which are retrieved and blended in a decision situation, provide the model with the flexibility to adapt its actions to very different climatic contexts, represented by the locations Stuttgart, Madrid, Stockholm, and Melbourne. Moreover, the model manages to find appropriate compromises if need satisfaction requires contradictory actions, such as in situations where satisfaction of the olfactory need requires opening the window and satisfaction of the thermal need requires keeping it closed. Despite its obvious complexity, the model must be considered to be a basic model, which restricts the immediate comparability of its results to human behavior data. However, the successfully applied plausibility checks clearly indicate the value of the cognitive approach to modeling human-building interaction.


Cognitive modeling Energy-relevant behavior Instance-based learning Prediction Social simulation 




Total activation


Total number of available actions


Total action space


Base level activation


Blended cost and benefits of an action


Blended value of an action


Costs associated with an action


Costs and Benefits of an instance


Clothing value


Decay factor


Number of associations between source slot and slots in memory


Ultimate goal of the model


Metabolic rate


Noise activation


Number of needs


Number of occurrences


Probability of retrieval of an instance


Penalization of activation due to partial matching


Partial matching scaling parameter


Perception threshold


Result stored to an instance


Total number of instances (belonging to an action)


Total number of slots of an instance


Associative strength (w/o index: maximum associative strength)


Spreading activation




Similarity parameter for slot comparison


Sensation rating




Utility of an instance


Spreading weight


Random draw out of [0,1]


Noise scaling parameter


Imprecision of retrieval (temperature parameter)





state State-related admissibility


switch Switch-related admissibility






Dimension to which an action belongs


hth need



i, j

ith and jth instance belonging to action m or m* and need h


kth instance belonging to need h, irrespective of action m


lth slot of an instance


Between slot l and instance k


mth action






pth occurrence of an instance in the past


Currently relevant need


State of an action

state x – state y

Change of states, from state x to state y









Considered worthwhile based on the blended value






This research is being funded by the Forschungsförderungsfond (FFF) Liechtenstein.

Compliance with Ethical Standards

Conflict of Interest

The author declares that he has no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Authors and Affiliations

  1. 1.Institute for Architecture and PlanningUniversity of LiechtensteinVaduzLiechtenstein

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