with the real world – design principles for

The paper addresses the question how a group of physically embodied robotic agents may originate meaning and language through adaptive language games. The main principles underlying the approach are sketched as well as the steps needed to implement these principles on physical agents. Some experimental results based on this implementation are presented. 1 Introduction In the past five years, a large number of robotic agents, i.e. physical systems capable of sensori-motor control, have been built in order to investigate a bottom-up approach to artificial intelligence (see the overview in [8]). Important results have been achieved, particularly by using behavior-oriented architectures [14] and learning methods based on neural networks [6] or genetic algorithms [3]. Nevertheless, it is still largely an open question how these robots may reach sufficient complexity in order to qualify as cognitive agents. Most of the experiments have focused on `low level' tasks like obstacle avoidance o...

Developmental robotics is an emerging field located at the intersection of robotics, cognitive science and developmental sciences. This paper elucidates the main reasons and key motivations behind the convergence of fields with seemingly disparate interests, and shows why developmental robotics might prove to be beneficial for all fields involved. The methodology advocated is synthetic and two-pronged: on the one hand, it employs robots to instantiate models originating from developmental sciences; on the other hand, it aims to develop better robotic systems by exploiting insights gained from studies on ontogenetic development. This paper gives a survey of the relevant research issues and points to some future research directions.

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This paper reports on an experiment in evolving the morphology of an artificial compound eye with 16 light sensors on a robot. A special robot was designed and constructed that is able to autonomously modify the angular positions of the individual light sensors within the compound eye. The task of the robot was to employ motion parallax to estimate a critical distance to obstacles. This task was achieved by adapting the morphology of the compound eye by an evolutionary algorithm while using a fixed neural network to control the robot. 1

New Robotics designates an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e.g. from control theory), designing agents in the New Robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics or design principles, that on the one hand capture theoretical insights about intelligent – adaptive – behavior, and on the other provide guidance in actually designing and building systems. In this paper we provide an overview of all the principles but focus on the principles of “ecological balance ” which concerns the relation between environment, morphology, materials, and control, and “sensory-motor coordination ” which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we will argue, artificial evolution together with morphogenesis is not only “nice to have ” but is in fact a necessary tool for designing embodied agents. 1.

In this paper we explore the possibility of quantitative analysis of sensory data and the interactions between the signals in different sensory channels as an agent interacts with the real world, in order to get a better intuition of these data which constitute, in a sense, the "raw material" that the neural system has to process. This will give us also a handle on formulating some of the design principles of autonomous agents, which we had worked out in earlier research, in a more quantitative way. As an example of an analysis, we employ information theoretic measures, such as the Shannon Entropy and the Mutual Information. We hope that the insights emerging from this research will eventually lead to a more formal description of some of the design principles of autonomous agents.

Abstract: We propose a modular architecture for autonomous robots which allows for the implementation of basic behavioral modules by both programming and training, and accommodates for an evolutionary development oftheinter-connections among modules. This architecture can implement highly complex controllers and allows for incremental shaping of the robot behavior. Our pro-posal is exempli ed and evaluated experimentally through a number of mobile robotic tasks involving exploration, battery recharging and object manipulation.

This paper presents a collective robotics application, which consists of making a pool of robots regroup objects that are distributed in their environment. The innovative aspect in our approach rests on a system integrating operationally autonomous robots that make the global task achieved by virtue of emergence and self-organization. 1 INTRODUCTION Our work fits in the framework of Bottom-Up Artificial Intelligence (Bottom-Up AI in short) and more particularly in that of Autonomous Agents. We are concerned with collective phenomena and their issues and more precisely the way to carry out solutions that allow a multi-robot system to achieve global tasks by virtue of emergence and self-organization. Our work is supported by two types of experiments, namely those involving multi-agent simulations and those involving real robots. Our paper precisely presents a collective robotics application, which consists of making a pool of autonomous robots regroup objects that are distributed in thei...

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