Energies 2015,8 11005 opportunities to incorporate more energy-related behaviors into simulation tools.In addition, this framework has the capability to evolve into BIM Another approach,Relative Agreement(RA)modeling,is an extension of a Bounded Confidence model [100]that can take into account different energy use characteristics of occupants,uncertainties about their opinion dynamics,and their interactions to each other.RA was defined and introduced by Deffuant et al.[101-103],and it can consider occupants as a population of agents that are selected randomly to interact with each other.In addition,each occupant (i.e.,agent)is characterized by two variables:its opinion,and its uncertainty [100,101].These two variables change over time.The ABM model developed by Azar and Menassa [12,87]is based on an RA concept.Additionally,Verplanken and Wood [104]and Gockeritz et al.[105]employed RA concepts to simulate pre-environmental behaviors of occupants in order to understand occupants'responses to the new energy characteristics of their built environment.Their results shows that an occupant's energy-conserving behavior is highly connected to his/her belief regarding other occupants'energy-conserving behaviors. Figure 2 shows the framework of current research.Although MAS tools have potential to simultaneously integrate ABM and other techniques for simulating occupancy related behavior [93], such MAS tools have not been directly addressed by literature.In this context,hybrid simulation approaches could be proposed. [28[75][86][81] [63][93]1 Markov Logic [98] Predictive Control [97]I ABM [80[78][91] 1[96 MAS [93]1 Fuzzy Logie [97][83][82]1 [12][87] [93]i Neural Network [97] RA[104[105] Nominal and Numerical Classifications[99] Figure 2.Framework of current research. 4.Improving Occupant Energy-Consuming Behaviors Improving occupant energy-consuming behaviors is a more cost-effective technique for cutting energy consumption than improving building's physical properties [18-20].Failure to improve occupant behaviors undermines the investment in retrofitting building envelopes and appliances since occupants define the success of such sustainable retrofitting projects [13,31].Furthermore,if occupants learn appropriate energy-saving behaviors,they can practice such behaviors in all buildings.Therefore,adopting energy-saving behaviors among occupants would then provide an opportunity for general energy savings within all built environments. Changing energy-use behaviors and motivating occupants to have sustainable behaviors are typically achieved by providing intervention tools for their behaviors and habits in order to improve the occupant's intentions and beliefs [45].Such interventions have used several techniques (e.g.,prompts,providing information and feedback,goal setting,and motivations)to attempt to improve occupant behavior,and each technique has had a level of success in reducing energy consumption [91,106-109].Generally, there are two main occupancy-focused intervention approaches(see Figure 3)[12,79]:(1)continuousEnergies 2015, 8 11005 opportunities to incorporate more energy-related behaviors into simulation tools. In addition, this framework has the capability to evolve into BIM. Another approach, Relative Agreement (RA) modeling, is an extension of a Bounded Confidence model [100] that can take into account different energy use characteristics of occupants, uncertainties about their opinion dynamics, and their interactions to each other. RA was defined and introduced by Deffuant et al. [101–103], and it can consider occupants as a population of agents that are selected randomly to interact with each other. In addition, each occupant (i.e., agent) is characterized by two variables: its opinion, and its uncertainty [100,101]. These two variables change over time. The ABM model developed by Azar and Menassa [12,87] is based on an RA concept. Additionally, Verplanken and Wood [104] and Göckeritz et al. [105] employed RA concepts to simulate pre-environmental behaviors of occupants in order to understand occupants’ responses to the new energy characteristics of their built environment. Their results shows that an occupant’s energy-conserving behavior is highly connected to his/her belief regarding other occupants’ energy-conserving behaviors. Figure 2 shows the framework of current research. Although MAS tools have potential to simultaneously integrate ABM and other techniques for simulating occupancy related behavior [93], such MAS tools have not been directly addressed by literature. In this context, hybrid simulation approaches could be proposed. Figure 2. Framework of current research. 4. Improving Occupant Energy-Consuming Behaviors Improving occupant energy-consuming behaviors is a more cost-effective technique for cutting energy consumption than improving building’s physical properties [18–20]. Failure to improve occupant behaviors undermines the investment in retrofitting building envelopes and appliances since occupants define the success of such sustainable retrofitting projects [13,31]. Furthermore, if occupants learn appropriate energy-saving behaviors, they can practice such behaviors in all buildings. Therefore, adopting energy-saving behaviors among occupants would then provide an opportunity for general energy savings within all built environments. Changing energy-use behaviors and motivating occupants to have sustainable behaviors are typically achieved by providing intervention tools for their behaviors and habits in order to improve the occupant’s intentions and beliefs [45]. Such interventions have used several techniques (e.g., prompts, providing information and feedback, goal setting, and motivations) to attempt to improve occupant behavior, and each technique has had a level of success in reducing energy consumption [91,106–109]. Generally, there are two main occupancy-focused intervention approaches (see Figure 3) [12,79]: (1) continuous