This paper discusses the phenomenological dimension of social understanding. The author’s general hypothesis is that complex forms of social unders standing that biological agents especially humans show are based on two s. mechanisms: 1 the bodily, experiential dynamics of emphatic resonance s. and 2 the biographic reconstruction of a communication situation. The latter requires the agent’s bodily experiences as the point of reference for the reconstruction process. This hypothesis is derived from discussions in philosophy, natural sciences, and cognitive science on the social embodiment of cognition and understanding. Evidence comes from studies on social cognition in primates, infants, and autistic people that are interpreted in terms of the ``mind-experiencing’ ’ hypothesis. The second part of the The writing of this paper was supported by an HCMr TMR research grant. Thanks to Erich Prem and an anonymous reviewer for their comments and suggestions, which helped me to improve a previous version of this paper. I am grateful to both the AI-Lab at GMD in Germany and the VUB AI-Lab in Belgium for giving me an environment for doing my research on social agents. The seesaw scenario was part of a student project s Claus Divossen, Susanne Jucknath, Michael Savels. in collaboration with the University of Bonn, Germany. I thank Sanjida O’Connell for discussions on empathy and theory of mind. Armin Deierling provided me with information about autism resources and discussed with me the question of how people with autism probably perceive the world.

We want to build robots capable of rich social interactions with humans, including natural communication and cooperation. This work explores how imitation as a social learning and teaching process may be applied to building socially intelligent robots, and summarizes our progress toward building a robot capable of learning how to imitate facial expressions from simple imitative games played with a human, using biologically inspired mechanisms. Our approach is heavily influenced by the ways human infants learn to communicate with their caregivers and understand the actions of others in intentional terms. Among the key ideas that we draw from work on the development of human social intelligence, the most crucial is the hypothesis that in human infants, imitative interactions, starting with facial mimicry, are a significant stepping-stone in developing appropriate social behavior, learning to predict other’s actions, and ultimately, understanding the intensions of others. 1

This paper is meant as a basis for discussion towards a framework for cognitive architectures integrating remembering, rehearsal, language and empathy. It describes the programmatic background of our concrete work on intelligent autonomous agents. The goal is to motivate a common framework which should inspire research on `artificial cognition' for autonomous robots as well as investigations on cognition in humans or other animals. 1 Introduction Our professional background are biology and artificial intelligence and we are mainly interested in the construction of intelligent autonomous agents based on biological and psychological findings and models. This paper outlines our research framework which grew out of considerations on cognition for artifacts, although we are aware that the successful implementation of these ideas is still a future goal. Instead of reviewing intensively literature of cognitive science and escpecially of cognitive psychology we focus on some points which are ...

We propose a causal Bayesian model of false belief reasoning in children. This model realizes theory of mind as the rational use of intuitive theories and supports causal prediction, explanation, and theory revision. The model undergoes an experience-driven false belief transition. We investigate the relationship between prediction, explanation, and surprise; this is used to interpret an empirical study of children’s explanations in an extension of the false belief task. Our study includes the standard outcome, surprising to younger children, and a novel “Psychic Sally ” condition that challenges older children with an unexpected outcome. In everyday life, humans constantly attribute unobservable mental states to one another, and use them to

This paper introduces a model of ‘theory of mind’, namely, how we represent the intentions and goals of others to optimise our mutual interactions. We draw on ideas from optimum control and game theory to provide a ‘game theory of mind’. First, we consider the representations of goals in terms of value functions that are prescribed by utility or rewards. Critically, the joint value functions and ensuing behaviour are optimised recursively, under the assumption that I represent your value function, your representation of mine, your representation of my representation of yours, and so on ad infinitum. However, if we assume that the degree of recursion is bounded, then players need to estimate the opponent’s degree of recursion (i.e., sophistication) to respond optimally. This induces a problem of inferring the opponent’s sophistication, given behavioural exchanges. We show it is possible to deduce whether players make inferences about each other and quantify their sophistication on the basis of choices in sequential games. This rests on comparing generative models of choices with, and without, inference. Model comparison is demonstrated using simulated and real data from a ‘stag-hunt’. Finally, we note that exactly the same sophisticated behaviour can be achieved by optimising the utility function itself (through prosocial utility), producing unsophisticated but apparently altruistic agents. This may be relevant ethologically in hierarchal game theory and coevolution.

Neuroethology is a branch of biology that studies the neural basis of naturally occurring animal behavior. This science, particularly a recent program called computational neuroethology, has a similar structure to the interdisciplinary endeavor of cognitive science. I argue that it would be fruitful to conceive of cognitive science as the computational neuroethology of humans. However, there are important differences between the two sciences, including the fact that neuroethology is much more comparative in its perspective. As a biological science, evolution is central to neuroethology and its target animals are studied in the context of their evolutionary relatives. The central goal of this paper is to argue that cognitive science can and ought to be more comparative in its approach to cognitive phenomena in humans. I show how the domain of cognitive science can be divided up into four different classes of cognitive behavior---individuated by the relative uniqueness of the behavior. I...

Abstract. Understanding intent is an important aspect of communication among people and is an essential component of the human cognitive system. This capability is particularly relevant for situations that involve collaboration among multiple agents or detection of situations that can pose a particular threat. We propose an approach that allows a physical robot to detect the intentions of others based on experience acquired through its own sensory-motor abilities. It uses this experience while taking the perspective of the agent whose intent should be recognized. The robot’s capability to observe and analyze the current scene employs a novel vision-based technique for target detection and tracking, using a non-parametric recursive modeling approach. Our intent recognition method uses a novel formulation of Hidden Markov Models (HMM’s) designed to model a robot’s experience and its interaction with the world while performing various actions. 1

Previous research shows that people assign latent goals or intentions to simple animated agents based on the motion behavior of these agents. We propose that human observers can infer that an animated agent has a partial state of belief about its environment and that observers use this information – in combination with the agent's observable behavior – to infer its goals. We conducted an experiment that showed that observers used line-of-sight cues – an agent's orientation relative to various objects in the environment, and the presence or absence of visual obstructions – to determine the content of an agent's state of belief about the location of objects. Our results are consistent with the hypothesis that human observers use line-of-sight cues to assign belief states to agents and that these belief states can be used to interpret agent behavior. We found that observer models that incorporated inferences about agents ’ beliefs outperformed an all-knowing observer model in describing human responses. Additionally, we found that human responses were most consistent with the behavior of a model that incorporates information about both orientation and line-of-sight obstructions.

The welfare of non-human primates used in research

Abstract not found