Högskolan i Skövde

From the perspective of cognitive robotics, this paper presents a modern interpretation of Newell’s (1973) reasoning and suggestions for why and how cognitive psychologists should develop models of cognitive phenomena. We argue that the shortcomings of current cognitive modelling approaches are due in significant part to a lack of exactly the kind of integration required for the development of embodied autonomous robotics. Moreover we suggest that considerations of embodiment, situatedness, and autonomy, intrinsic to cognitive robotics, provide an appropriate basis for the integration and theoretic cumulation that Newell argued was necessary for psychology to mature. From this perspective we analyse the role of embodiment and modes of situatedness in terms of integration, cognition, emotion, and autonomy. Four complementary perspectives on embodied and situated cognitive science are considered in terms of their potential to contribute to cognitive robotics, cognitive science, and psychological theorizing: minimal cognition and organization, enactive perception and sensorimotor contingency, homeostasis and emotion, and social embedding. In combination these perspectives provide a framework for cognitive robotics, not only wholly compatible with the original aims of cognitive modelling, but as a more appropriate methodology than those currently in common use within psychology.

The interaction of brain, body, and environment can result incomplex behavior with rich dynamics, even for relatively simpleagents. Such dynamics are, however, often difficult to analyze.In this article, we explore the case of a simple simulated roboticagent, equipped with a reactive neurocontroller and an energylevel, which the agent has been evolved to recharge. A dynamicalsystems analysis shows that a non-neural internal state (energylevel), despite its simplicity, dynamically modulates the behavioralattractors of the agent—environment system, such thatthe robot's behavioral repertoire is continually adapted toits current situation and energy level. What emerges is a dynamic,non-deterministic, and highly self-organized action selectionmechanism, originating from the dynamical coupling of four systems(non-neural internal states, neurocontroller, body, and environment)operating at very different timescales.

The interaction of brain, body and environment can result in complex behavior with rich dynamics even for relatively simple agents. Such dynamics are, however, often notoriously difficult to analyze. In this paper we explore the case of a simple simulated robotic agent, equipped with a reactive neurocontroller and an energy level, that the agent has been evolved to re-charge. A dynamical systems analysis, shows that a non-neural internal state (energy level), despite its simplicity, dynamically modulates the agent-environment system’s behavioral attractors, such that the robot’s behavioral repertoire is continually adapted to its current situation and energy level.

In this paper we suggest a biologically inspired approach to flexible behavior through emotion modeling. We consider emotion to emerge from relational interaction of body, nervous system and world, through sensory-motor attunement of internal parameters to concern-relevant relationships. We interpret such relationships with the notions of collective variable and control parameters. We introduce a simple robotic implementation of this model of appraisal, following the techniques of evolutionary neuro-robotics.

Emotions can be considered inextricably linked to embodied appraisals - perceptions of bodily states that inform agents of how they are faring in the world relative to their own well-being. Emotion-appraisals are thus relational phenomena the relevance of which can be learned or evolutionarily selected for given a reliable coupling between agent-internal and environmental states. An emotion-appraisal attentional disposition permits agents to produce behaviour that exploits such couplings allowing for adaptive agent performance across agent-environment interactions. This chapter discusses emotions in terms of dynamical processes whereby attentional dispositions are considered central to an understanding of behaviour. The need to reconcile a dynamical systems perspective with an approach that views emotions as attentional dispositions representative of embodied relational phenomena (embodied appraisals) is argued for. Attention and emotion are considered to be features of adaptive agent behaviour that are interdependent in their temporal, structural and organizational relations.

In order to explain and model emotion we need to attend to the role internal states play in the generation of behavior. We argue that motivational and perceptual roles emerge from the dynamical interaction between physiological processes, sensory-motor processes and the environment. We investigate two aspects inherent to emotion appraisal and response which rely on physiological process: the ability to categorize relations with the environment and to modulate response generating different action tendencies.

Adaptive agents exhibit tightly coupled interactions between nervous system, body and environment. Parisi recently suggested that the current focus on sensorimotor interaction between agent and environment needs to be complemented by an "internal robotics", i.e. modeling of the interaction between internal physiology and nervous system in, for example, emotional mechanisms. The dynamical systems notion of "collective variables" can help understanding such interactions. In emotions physiological states are key parameters that trace the global dynamic concern relevance of the situation. Such variables may be key, in adaptive systems, to monitoring and controlling the agent's interaction with the external environment. We show in a simple robotic simulation that the neural controller can self-organize to exploit the dynamical regularities traced by these variables. We conclude this can prove to be a useful technique in robots and animals, towards evolving emotion-based adaptive behaviors.