# Enhancing Human-Agent Interaction via Artificial Agents That Speculate About the Future
## 2 Background  
### Theoretical Work  
The question of what makes a conversational agent or interface \"intelligent\" is a complicated one [29]. From a theoretical perspective, the broad notion that such intelligence would entail having an artificial agent that could anticipate events in the real world before they occur has a long history [30; 31]. More recently, there have been theoretical attempts to address it in the fields of HAI and HRI, some of which have applicability to the problem we are addressing here.  
For instance, [PERSON] (2023) argued that the concept of social cohesion (introduced in Section 1) should be seen more as \"virtual bargaining\" between two parties. In short, the collective meaning inherent in social communication is not defined by any individual person (or artificial agent for that matter), and as such, communicating about the future should be viewed as a sort of \"negotiation\" between conversational partners about what is important to focus on (versus what is not), based on known social norms [32]. After all, humans are not really free to do \"whatever they want\", even though there is a lot of flexibility within the constraints of social and cultural systems. Sometimes we do not even clearly articulate our speech on purpose (e.g., dialect use, slang), in order convey hidden meaning or signal status to others [7]. As such, we may be placing too heavy a burden on our artificial agents by omitting the fact that what we say is not always the \"real point\" when we engage in efforts to create more natural AI interactions by focusing on what our artificial agents say, since there is so much being sub-communicated in real human interactions that has to be interpreted by both parties. In other words, it is not a fixed set of \"rules\" that govern human behavior, but rather a _negotiation_ about the future that determines the \"rules\" in the real world [32]. Speculation, in that sense, is a form of negotiation. Thus, if an artificial conversational agent can negotiate the rules through speculation, then it may possibly have a greater chance of successful interaction with humans. Suffice it to say, there are some intriguing parallels between our notion of speculating about the future via anticipatory speech and [PERSON]'s concept of social negotiation.  
Beyond the above, some researchers have recently looked into creating virtual simulations of cooperation between human infants and their caregivers (including both verbal and non-verbal interaction) as a way of understanding simple cooperative scenarios prior to the social complexity we typically see among human adults [33; 34]. The idea is that developing a stronger theoretical basis through such virtual simulation will identify the basic components of social cooperation that could then potentially serve as building blocks for improved artificial agents and robots. The strategy of using these kinds of virtual simulations to model more complex social scenarios has some similarities to this research here, though our work is more experimental in nature (see the next section).  
Of course, there are other studies in existence related to coordinated joint actions between humans and robots conducted in lab settings meant to understand the theoretical basis of physical coordination, but those focus mainly on the mechanics of the physical action itself (e.g., kinematics) [35]. Though such coordination can at times involve speech communication, that is not the focus, nor are those studies designed specifically to study speech interaction [10; 36]. As such, that research has limited applicability to our specific problem scenario here, which does not necessarily require any sort of physical interaction to occur. Indeed, user models in HRI/HAI cover many modes of interaction with social robots and virtual avatars, not all of which are physical in nature, even when applied to a physically embodied robot [37].