There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting collective behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of collective robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations. 1

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...

This paper proposes a research direction to study the development of `artificial social intelligence' of autonomous robots which should result in `individualized robot societies'. The approach is highly inspired by the `social intelligence hypothesis', derived from the investigation of primate societies, suggesting that primate intelligence originally evolved to solve social problems and was only later extended to problems outside the social domain. We suggest that it might be a general principle in the evolution of intelligence, applicable to both natural and artificial systems. Arguments are presented why the investigation of social intelligence for artifacts is not only an interesting research issue for the study of biological principles, but may be a necessary prerequisite for those scenarios in which autonomous robots are integrated into human societies, interacting and communicating both with humans and with each other. As a starting point to study experimentally the development ...

The paper proposes a set of principles and a general architecture that may explain how language and meaning may originate and complexify in a group of physically grounded distributed agents. An experimental setup is introduced for concretising and validating specific mechanisms based on these principles. The setup consists of two robotic heads that watch a scene in which a robot moves around in its ecosystem. The first results from experiments showing the emergence of distinctions, of a lexicon, and of primitive syntactic structures are reported. 1 Introduction Artificial Intelligence research has made remarkable progress the last decades by showing how operations over symbolic models may explain various aspects of intelligent behavior, such as planning, problem solving, natural language processing, etc. However, the problem of the origin of these symbolic models has so far not been adequately addressed. Most of the time it is the programmer who designs formalisms and datastructures, ...

All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dissertation

This chapter addresses embodied social interaction inlif6 like agents. Embodiment is discussedf rom both arti cial intelligence and psychology viewpoints. Di#erent degreesof embodiment in biological, virtual and robotic agents are discussed, given the example of a bottomup, behavior-oriented, dynamic control of virtual robots. A `dancing with strangers' experiment shows how the same principles can be applied to physical robot-human interaction. We then discuss the issue of sociality which di#ers in di#erent academic communities with respect to which roles are attributed to genes, memes, and the individual embodied agent.

This paper builds on a previous review of significant research on adaptive behavior in animats. It summarizes the current state of the art and suggests some directions likely to provide interesting results in the near future. 1 Introduction An animat is a simulated animal or a real robot whose rules of behavior are inspired by those of animals. It is usually equipped with sensors, with actuators, and with a behavioral control architecture that allow it to react or to respond to variations in its environment (internal or external), notably to those that might impair its chances of survival. The behavior of an animat is what the animat does. This is characterized by a sequence of actions which reflects the dynamic interplay between the animat and its environment, mediated through the animat's sensors and actuators. The behavior of an animat is adaptive so long as it allows the animat to survive or to fulfill its mission. This requires that the animat's essential variables be monitored a...

. The paper explores a biologically inspired definition of intelligent autonomous agents. Intelligence is related to whether behavior of a system contributes to its self-maintenance. Behavior becomes more intelligent (or copes with more ecological pressures) when it is capable to create and use representations. The notion of representation should not be restricted to formal expressions with a truththeoretic semantics. The dynamics at various levels of intelligent systems plays an essential role in forming representations. Keywords: intelligence, self-organisation, representation, complex dynamical systems. 1 Introduction What exactly are intelligent autonomous agents? Unless we have some good criteria that are clear targets for the field, it will both be difficult to judge whether we have achieved our aims or to set intermediate milestones to measure whether progress has been made. The goal of this paper is to present a definition of intelligent autonomous agents. The definition has t...

The paper proposes an architecture for the online evolution of new behavioral competences on a robotic agent. Some experimental results for evolving a set of primitive behaviors are presented. Introduction A central question in ALife research is how new complexity and new functionality may emerge [Steels1994]. Selectionism and self-organisation have so far been put forward as the key explanatory principles [Langton1989]. These principles have been been applied at many level of biological systems, from the chemical reactions that explain the origin of life [Kaufmann1993] to the interaction between individuals in societies [Deneubourg1993]. This paper explores in how far selectionism and selforganisation may lead to the build up of behavioral complexity in animals. In the tradition of Alife research, this exploration takes place by building artificial systems, i.c. robotic agents. There has already been a large amount of work attempting to use selectionist techniques for evolving behavi...

Many researchers are working towards the goal of a semantic Web --- a Web that provides information in a way that is useful to artificial intelligences.