Embodiment has become an important concept in many areas of cognitive science. There are, however, very different notions of exactly what embodiment is and what kind of body is required for what kind of embodied cognition. Hence, while many would agree that humans are embodied cognizers, there is much less agreement on what kind of artefact could be considered as embodied. This paper identifies and contrasts five different notions of embodiment which can roughly be characterized as (1) structural coupling between agent and environment, (2) historical embodiment as the result of a history of structural coupling, (3) physical embodiment, (4) `organismoid' embodiment, i.e. organism-like bodily form (e.g., humanoid robots), and (5) organismic embodiment of autopoietic, living systems. 1.

The addition of emotions may be the key to producing rational behavior in autonomous agents. For situated agents, a different perspective on learning is proposed which relies on the agent's ability to react in an emotional way to its dynamically changing environment. Here an architecture of mind is presented with the ability to display adaptive emotional states of varying types and intensities, and an implementation, "Conscious" Mattie (CMattie), of this architecture is discussed. Using this architecture, CMattie will be able to interact with her environment in a way that includes emotional content at a basic level. In addition she will learn more complex emotions which will enable her to react to her situation in a more complex manner. A general description is given of the emotional mechanisms of the architecture and its effects on learning are explained.

This paper gives an overview of the bottom-up approach to artificial intelligence (AI), commonly referred to as behavior-oriented AI. The behavior-oriented approach, with its focus on the interaction between autonomous agents and their environments, is introduced by contrasting it with the traditional approach of knowledge-based AI. Different notions of autonomy are discussed, and key problems of generating adaptive and complex behavior are identified. A number of techniques for the generation of behavior are introduced and evaluated regarding their potential for realizing different aspects of autonomy as well as adaptivity and complexity of behavior. It is concluded that in order to realize truly autonomous and intelligent agents, the behavior-oriented approach will have to focus even more on life-like qualities in both agents and environments.

Integration of major cognitive capabilities and behavioral capabilities is crucial for robots to perform harder, general tasks. Several requirements are raised in this paper: (1) a successful integration of such capabilities need to start with an architecture that is suited for integration, (2) the development of each individual capability must be an integral process of overall integration process, and (3) the content-level integration process must be fully automated. The developmental approach to intelligent robots is presented in this paper as a way for integrating cognitive and behavioral capabilities in an automated way. This approach is motivated by human cognitive development from infant to adult. Central in the approach is the methodology for sensor-effector-rich robots to perform general-purpose, autonomous, incremental learning directly using their sensors and effectors through interactions with the realworld environment. In other words, the objective is to fully automate the learning process, so that the robots can learn in an automatic mode that is close to the way animals (and humans) learn. A comparison between the developmental approach and other existing approaches is provided.

Creative products are generally recognised as satisfying two requirements: firstly they are useful, and secondly they are novel. Much effort in AI and design computing has been put into developing systems that can recognise the usefulness of the products that they generate. In contrast, the work presented in this thesis has concentrated on developing computational systems that are able to recognise the novelty of their work. The research has shown that when computational systems are given the ability to recognise both the novelty and the usefulness of their products they gain a level of autonomy that opens up new possibilities for the study of creative behaviour in single agents and the emergence of social creativity in multi-agent systems. The work

Biorobotic research seeks to develop new robotic technologies based on the performance of human and animal neuromuscular systems. The development of one component of a biorobotic system, an artificial muscle and tendon, is documented here. The device is based on known static and dynamic properties of biological muscle and tendon which were extracted from the literature and used to mathematically describe the unique force, length, and velocity relationships. As biological tissue exhibits wide variation in performance, ranges are identified which encompass typical behavior for design purposes. The McKibben pneumatic actuator is proposed as the contractile element of the artificial muscle. A model is presented that includes not only the geometric properties of the actuator, but also the material properties of the actuator's inner bladder and frictional effects. Experimental evidence is presented that validates the model and shows the force-length properties to be muscle-like, while the force-velocity properties are not. The addition of a hydraulic damper is proposed to improve the actuator's velocity-dependent properties, complete with computer simulations and experimental evidence validating the design process. Furthermore, an artificial tendon is proposed to serve as connective tissue between the artificial muscle and a skeleton. A series of experimental tests verifies that the design provides suitable tendon-like performance. A complete model of the artificial musculo-tendon system is then presented which predicts the expected force-length-velocity performance of the artificial system. Based on the mode...

Today's `autonomous' robots only have very limited autonomy and are in fact very much under the control of the `environmental puppeteer', i.e their behaviour is determined, via virtual strings, by environmental conditions. Hence, it has been stated as the goal of modern scientific robotics to "cut the strings and give the robot its autonomy". Different notions of autonomy in artefacts and living systems are examined in this paper, and different aspects/dimensions of autonomy are identified and illustrated with examples from connectionist robot control. A connectionist architecture is introduced that aims to increase robotic autonomy through integration of connectionist self-organisation/learning with the enactive view of structural coupling between environment and agent. In the resulting robot control architecture it is the environment that is pulling the strings, but the agent that develops them and dynamically decides which of them to use in a particular situation. Hence...

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It has been proved to be extremely challenging for humans to program a robot to such a sufficient degree that it acts properly in a typical unknown human environment. This is especially true for a humanoid robot due to the very large number of redundant degrees of freedom and a large number of sensors that are required for a humanoid to work safely and effectively in the human environment.

Here we describe an architecture for an autonomous software agent designed to model a broad spectrum of human cognitive and affective functioning. In addition to featuring “consciousness ” the architecture accommodates perception, several forms of memory, emotions, action-selection, deliberation, ersatz language generation, several form of learning, and metacognition. One such software agent, IDA, embodying much of this architecture, is up and running. IDA’s “consciousness” module is based on global workspace theory, allowing it to select relevant resources with which to deal flexibly with both exogenous and endogenous stimuli. Within this architecture emotions implement IDA’s drives, her 1 primary motivations. Offering one possible architecture for a fully functioning artificial mind, IDA constitutes an early attempt at the exploration of design space and niche space. The design of the IDA architecture spawns hypotheses concerning human cognition and affect that can serve to guide the research of cognitive scientists and neuroscientists. One such hypothesis is that consciousness is discrete.