Abstract | In this paper we describe the evolution of a discrete-time recurrent neural network to control a real mobile robot. In all our experiments the evolutionary procedure is carried out entirely on the physical robot without human intervention. We showthat the autonomous development of a set of behaviors for locating a battery charger and periodically returning to it can be achieved by lifting constraints in the design of the robot/environment interactions that were employed in a preliminary experiment. The emergent homing behavior is based on the autonomous development ofaninternal neural topographic map (which is not pre-designed) that allows the robot to choose the appropriate trajectory as function of location and remaining energy.

The problem of the validity of simulation is particularly relevant for methodologies that use machine learning techniques to develop control systems for autonomous robots, like, for instance, the Artificial Life approach named Evolutionary Robotics. In fact, despite that it has been demonstrated that training or evolving robots in the real environment is possible, the number of trials needed to test the system discourage the use of physical robots during the training period. By evolving neural controllers for a Khepera robot in computer simulations and then transferring the obtained agents in the real environment we will show that: (a) an accurate model of a particular robot-environment dynamics can be built by sampling the real world through the sensors and the actuators of the robot; (b) the performance gap between the obtained behaviors in simulated and real environment may be significantly reduced by introducing a "conservative" form of noise; (c) if a decrease in per...

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In this article we describe a methodology for evolving neurocontrollers of autonomous mobile robots without human intervention. The presentation, which spans from technological and methodological issues to several experimental results on evolution of physical mobile robots, covers both previous and recent work in the attempt to provide a uni ed picture within which the reader can compare the effects of systematic variations on the experimental settings. After describing some key principles for building mobile robots and tools suitable for experiments in adaptive robotics, we give an overview of different approaches to evolutionary robotics and present our methodology. We start reviewing two basic experiments showing that different environments can shape very different behaviors and neural mechanisms under very similar selection criteria. We then address the issue of incremental evolution in two different experiments from the perspective of changing environments and robot morphologies. Finally, we investigate the possibility of evolving plastic neurocontrollers and analyze an evolved neurocontroller that relies on fast and continuously changes synapses characterized by dynamic stability. We conclude by reviewing the implications of this methodology for engineering, biology, cognitive science, and artificial life, and point at future directions of research.

This paper presents an analysis of an artificially evolved dynamical network-based control system for a simulated autonomous mobile robot engaged in simple visually guided tasks.

In this paper I claim that one of the main characteristics that makes the Evolutionary Robotics approach suitable for the study of adaptive behavior in natural and artificial agents is the possibility to rely largely on a self-organization process. Indeed by using Artificial Evolution the role of the designer may be limited to the specification of a fitness function which measures the ability of a given robot to perform a desired task. From an engineering point of view the main advantage of relying on self-organization is the fact that the designer does not need to divide the desired behavior into simple basic behaviors to be implemented into separate layers (or modules) of the robot control system. By selecting individuals for their ability to perform the desired behavior as a whole, simple basic behaviors can emerge from the interaction between several processes in the control system and from the interaction between the robot and the environment. From the point of view of ...

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Behaviors such as exploration and homing, that seemingly demand a complex control system, only require a perceptron that connects a robot's sensors to its motors. This is shown by evolving such neurocontrollers for the Khepera robot. An exploitation of the robot's perception of the environment's geometrical shape allows the robot to encode time, even though explicitly it is not presented with the time and there are no recurrent connections in the neurocontroller. In a biological context, the robotics approach to show sufficient requirements for obtaining specific behaviors suggest that some biological experiments have to be re-done in order for the conclusions drawn from these biological experiments to be valid.

this paper, I shall present a survey of some work done in Evolutionary Robotics by myself and in collaboration with some colleagues, mainly Francesco Mondada and Stefano Nolfi. This paper intends to be a gentle introduction to Evolutionary Robotics and, therefore, it will not include much technical detail which interested readers will find in cited articles. The presentation will be structured according to two issues which I feel are important for practical use and application of Evolutionary Robotics:

In this paper I explore the hypothesis that some of today robots might possess a form of consciousness whose substrate is a mere algorithm. First, consciousness is defined within an evolutionary framework as awareness of one's own state in relation to the external environment. Then, the basic prerequisites for such conscious activity are discussed, namely embodiment, autonomy, and adaptation mechanisms. Artificial evolution, rather than evolutionary optimisation, is presented as a viable methodology to create conscious robots, accompanied by some examples of behaviours of artificially evolved robots. Finally, I argue that what might be problematic with the concept of robot consciousness is not the robot, but the notion of consciousness itself. 1 Paving the Road to Robot Consciousness Could the ordered list of operations which forms any computer algorithm constitute the basis of consciousness for a robot? "Of course not", would be the sensible answer probably given by most readers with...