**2.2 A variety of computerization configurations**

Although the previous sections have presented the types of gaming simulations in a somewhat binary way, simply distinguishing between pure computer simulations and non-computer-based games (haptic game, role-playing game,…), in practice there is a whole continuum between computer simulation and haptic games. In the 1960s, Padioleau [22] presented this continuum and classified gaming simulation applications used in the field of political sociology into three categories: those involving only humans (including games for educational use, strategic games for "decision support" and games for theoretical experimentation (e.g. [23])), those involving "mixed simulations" in which (human) participants use computers, and finally "computer simulations". Two decades later, Crookall et al. [15] proposed a classification designed to account for human-computer interactions in a computer simulation environment.4 This classification distinguishes between two dimensions (**Figure 2**): whether the human or the computer controls the simulation (control of the simulated events and of the overall progress of the simulation) and which type of interaction prevails (humanto-human interaction or human-to-computer interaction).


#### **Figure 2.**

*Classification of human-machine interactions in a computer simulation environment (source: [15], as cited in [17]).*

<sup>4</sup> In the Crookall et al. [15] classification, since it focuses on human-computer interactions, games with no computing component are not considered.

The four categories in this classification are as follows:


This classification provides a meaningful way of understanding the main interaction modes that exist at the interface between simulation and "played simulation". Yet, the ways of interacting with a simulation have evolved since this early classification; technological advances prompt a rethink of the categories proposed by Crookall et al.. In particular, with regard to the CBS category, when it comes to simulations involving several players, todays' technology allows each player to interact individually with a simulation that is shared among several players. In this configuration, human-tohuman interactions exist, even though it happens through a computer interface, which usually represents the players in the virtual world by a computer avatar.

Le Page et al. [24] analysed in more detail these inter-player interactions that take place through the computer. To do this, they attempted to characterise the decisionmaking agents in simulation and gaming artefacts and the types of decision-making agents. The authors consider that the decision can be made either by a human or by a computer program, and that in a played simulation, a human (or a group of humans) can adopt a computer avatar that represents them in the virtual world. They identified four possible types of decision-making agents (from left to right in **Figure 3**):


#### **Figure 3.**

*Types of decision-making agents [24].*

<sup>5</sup> Crookall et al. specify that the CCS category relates to simulations in which a group of people interact with each other either to comment on what is happening or to choose a path for the next sequence of the simulation (as in a "choose your own adventure book" but instead of having an individual reader, a whole group of people choose the continuation of the simulation).

(i) the human agent, for whom the decision is 100% human and which has no computer avatar; (ii) the composite agent, for whom the decision is also 100% human but who is represented by a non-decision-making avatar in the virtual world; (ii) the hybrid composite agent, for whom some of the decisions are made by a human and some by a computer program (the computer avatar is then partially decisionmaking); and (iv) the computer agent whose decisions are 100% derived from a computer program.

To draw a parallel with the previous classification, 100% human composite agent category corresponds to CAS. Conversely, 100% computer agents correspond to CDS, or possibly CCS where the means of control involves something other than the agents. The Le Page et al. classification highlights the range of intermediate configurations that exist between these two end points of the continuum. Within the CBS and CAS categories, there are systems today that include some computer agents and some human or composite agents. In the CBS category, there are also systems that involve only hybrid composite agents. These considerations also relate with ongoing research on hybrid applications, which aims to combine the "space for discussion and social interaction" dimension of games and the "exploratory capabilities" dimension of computer simulations. In this research sector, hybrid game boards for example seek to develop haptic games that use automatic recognition system for in-game actions. Game boards of this kind can be used to design interaction systems between human and computer agents that are much more fluid, or to design new forms of composite agents.

This short literature review shows that the opportunities for interaction between humans through computer technology and digital interfaces have increased significantly, and this raises the question of the link between computer technology and the learning potential of the tool.
