Social Interaction Under the Free Energy Principle: A Cognitive Robotics Approach

Many things we do or think involve other people. We (strive to) understand, predict, and coordinate our actions with them in various social contexts. Many scientists investigate related cognitive mechanisms of social behavior. However, how individual and collective dynamics allow us to coordinate our actions in different social settings is not fully understood. Recently, the free energy principle has drawn attention with the expectation that it could provide a unified theory of the brain to model action, perception, and learning, among other cognitive skills. This thesis investigates how action, perception of actions, and learning of two agents translate into a mutual social context. I use a neurorobotics experimental setup to systematically study dyadic synchronized imitative interaction by extending the frameworks of predictive coding and active inference under the free energy principle. In the proposed model, the top-down processes encode prior beliefs, which allow robots to generate an action and predict the future action of the other robot. The two robots observe each other’s actions through a reciprocally coupled action-perception loop. The bottom-up inference process approximates the posterior belief by minimizing free energy whenever prediction and observation differ. In a wide range of experiments, I explored how regulating free energy complexity, i.e., the divergence of the prior and the approximate posterior belief can guide individual behavior and behavior coordination in the dyadic context. I show that three types of dyadic behavior coordination dynamically emerge due to the coregulated optimization processes in the robots’ reciprocally coupled action-perception loop, including (1) one robot is leading and the other robot is following (and vice versa), (2) robots are ignoring each other, and (3) robots are spontaneously taking turns in leading and following. Finally, I show that slowly oscillating the regulation of free energy complexity during an interaction leads to rather agreed-upon, intentional turntaking behavior. The contribution of this thesis is shedding light on the mechanisms under the free energy principle that lead to the dynamic emergence of different types of behavior coordination in imitative interaction. By discussing qualitative and quantitative differences between those behaviors, including the aforementioned two types of turn-taking, essential aspects of autonomous behavior coordination in synthetic and empirical studies are clarified.Okinawa Institute of Science and Technology Graduate Universit

Turn-Taking Mechanisms in Imitative Interaction: Robotic Social Interaction Based on the Free Energy Principle

This study explains how the leader-follower relationship and turn-taking could develop in a dyadic imitative interaction by conducting robotic simulation experiments based on the free energy principle. Our prior study showed that introducing a parameter during the model training phase can determine leader and follower roles for subsequent imitative interactions. The parameter is defined as , the so-called meta-prior, and is a weighting factor used to regulate the complexity term versus the accuracy term when minimizing the free energy. This can be read as sensory attenuation, in which the robot’s prior beliefs about action are less sensitive to sensory evidence. The current extended study examines the possibility that the leader-follower relationship shifts depending on changes in during the interaction phase. We identified a phase space structure with three distinct types of behavioral coordination using comprehensive simulation experiments with sweeps of of both robots during the interaction. Ignoring behavior in which the robots follow their own intention was observed in the region in which both s were set to large values. One robot leading, followed by the other robot was observed when one was set larger and the other was set smaller. Spontaneous, random turn-taking between the leader and the follower was observed when both s were set at smaller or intermediate values. Finally, we examined a case of slowly oscillating in anti-phase between the two agents during the interaction. The simulation experiment resulted in turn-taking in which the leader-follower relationship switched during determined sequences, accompanied by periodic shifts of s. An analysis using transfer entropy found that the direction of information flow between the two agents also shifted along with turn-taking. Herein, we discuss qualitative differences between random/spontaneous turn-taking and agreed-upon sequential turn-taking by reviewing both synthetic and empirical studies.journal articl

Leading or Following? Dyadic Robot ImitativeInteraction Using the Active Inference Framework

This study investigated how social interaction among robotic agents changes dynamically depending on the individual belief of action intention. In a set of simulation studies, we examine dyadic imitative interactions of robots using a variational recurrent neural network model. The model is based on the free energy principle such that a pair of interacting robots find themselves in a loop, attempting to predict and infer each other\u27s actions using active inference. We examined how regulating the complexity term to minimize free energy determines the dynamic characteristics of networks and interactions. When one robot trained with tighter regulation and another trained with looser regulation interact, the latter tends to lead the interaction by exerting stronger action intention, while the former tends to follow by adapting to its observations. The study confirms that the dyadic imitative interaction becomes successful by achieving a high synchronization rate when a leader and a follower are determined by developing action intentions with strong belief and weak belief, respectively

A Neurorobotics Approach to Investigating the Emergence of Communication in Robots

This paper introduces our approach to building a robot with communication capability based on the two key features: stochastic neural dynamics and prediction error minimization. A preliminary experiment showed that the humanoid robot was able to imitate other\u27s action by means of those key features. In addition, we found that some sorts of communicative patterns emerged between two robots in which the robots inferred the intention of another agent behind the sensory observation

Turn-Taking Mechanisms in Imitative Interaction: Robotic Social Interaction Based on the Free Energy Principle

This study explains how the leader-follower relationship and turn-taking could develop in a dyadic imitative interaction by conducting robotic simulation experiments based on the free energy principle. Our prior study showed that introducing a parameter during the model training phase can determine leader and follower roles for subsequent imitative interactions. The parameter is defined as w, the so-called meta-prior, and is a weighting factor used to regulate the complexity term versus the accuracy term when minimizing the free energy. This can be read as sensory attenuation, in which the robot’s prior beliefs about action are less sensitive to sensory evidence. The current extended study examines the possibility that the leader-follower relationship shifts depending on changes in w during the interaction phase. We identified a phase space structure with three distinct types of behavioral coordination using comprehensive simulation experiments with sweeps of w of both robots during the interaction. Ignoring behavior in which the robots follow their own intention was observed in the region in which both ws were set to large values. One robot leading, followed by the other robot was observed when one w was set larger and the other was set smaller. Spontaneous, random turn-taking between the leader and the follower was observed when both ws were set at smaller or intermediate values. Finally, we examined a case of slowly oscillating w in anti-phase between the two agents during the interaction. The simulation experiment resulted in turn-taking in which the leader-follower relationship switched during determined sequences, accompanied by periodic shifts of ws. An analysis using transfer entropy found that the direction of information flow between the two agents also shifted along with turn-taking. Herein, we discuss qualitative differences between random/spontaneous turn-taking and agreed-upon sequential turn-taking by reviewing both synthetic and empirical studies

Turn-Taking Mechanisms in Imitative Interaction: Robotic Social Interaction Based on the Free Energy Principle

This study explains how the leader-follower relationship and turn-taking could develop in a dyadic imitative interaction by conducting robotic simulation experiments based on the free energy principle. Our prior study showed that introducing a parameter during the model training phase can determine leader and follower roles for subsequent imitative interactions. The parameter is defined as w, the so-called meta-prior, and is a weighting factor used to regulate the complexity term versus the accuracy term when minimizing the free energy. This can be read as sensory attenuation, in which the robot’s prior beliefs about action are less sensitive to sensory evidence. The current extended study examines the possibility that the leader-follower relationship shifts depending on changes in w during the interaction phase. We identified a phase space structure with three distinct types of behavioral coordination using comprehensive simulation experiments with sweeps of w of both robots during the interaction. Ignoring behavior in which the robots follow their own intention was observed in the region in which both ws were set to large values. One robot leading, followed by the other robot was observed when one w was set larger and the other was set smaller. Spontaneous, random turn-taking between the leader and the follower was observed when both ws were set at smaller or intermediate values. Finally, we examined a case of slowly oscillating w in anti-phase between the two agents during the interaction. The simulation experiment resulted in turn-taking in which the leader-follower relationship switched during determined sequences, accompanied by periodic shifts of ws. An analysis using transfer entropy found that the direction of information flow between the two agents also shifted along with turn-taking. Herein, we discuss qualitative differences between random/spontaneous turn-taking and agreed-upon sequential turn-taking by reviewing both synthetic and empirical studies