Populations of simulated agents controlled by dynamical neural networks are trained by artificial evolution to access linguistic instructions and to execute them by indicating, touching, or moving specific target obje...
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Populations of simulated agents controlled by dynamical neural networks are trained by artificial evolution to access linguistic instructions and to execute them by indicating, touching, or moving specific target objects. During training the agent experiences only a subset of all object/action pairs. During postevaluation, some of the successful agents proved to be able to access and execute also linguistic instructions not experienced during training. This owes to the development of a semantic space, grounded in the sensory motor capability of the agent and organized in a systematized way in order to facilitate linguistic compositionality and behavioral generalization. Compositionality seems to be underpinned by a capability of the agents to access and execute the instructions by temporally decomposing their linguistic and behavioral aspects into their constituent parts (i.e., finding the target object and executing the required action). The comparison between two experimental conditions, in one of which the agents are required to ignore rather than to indicate objects, shows that the composition of the behavioral set significantly influences the development of compositional semantic structures.
In this paper, we study the problem of exploration and navigation in an unknown environment from an evolutionary swarm robotics perspective. In other words, we search for an efficient exploration and navigation strate...
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In this paper, we study the problem of exploration and navigation in an unknown environment from an evolutionary swarm robotics perspective. In other words, we search for an efficient exploration and navigation strategy for a swarm of robots, which exploits cooperation and self-organisation to cope with the limited abilities of the individual robots. The task faced by the robots consists in the exploration of an unknown environment in order to find a path between two distant target areas. The collective strategy is synthesised through evolutionary robotics techniques, and is based on the emergence of a dynamic structure formed by the robots moving back and forth between the two target areas. Due to this structure, each robot is able to maintain the right heading and to efficiently navigate between the two areas. The evolved behaviour proved to be effective in finding the shortest path, adaptable to new environmental conditions, scalable to larger groups and larger environment size, and robust to individual failures.
Automatic off-line design is an attractive approach to implementing robot swarms. In this approach, a designer specifies a mission to be accomplished by the swarm, and an optimization process generates suitable contro...
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Automatic off-line design is an attractive approach to implementing robot swarms. In this approach, a designer specifies a mission to be accomplished by the swarm, and an optimization process generates suitable control software for the individual robots through computer-based simulations. Most relevant literature has focused on effectively transferring control software from simulation to physical robots. Here, we investigate 1) whether the design methods that generate control software are transferable across robot platforms and 2) whether control software generated via such methods is itself transferable. We experiment with two ground mobile platforms with equivalent functional capabilities. Our measure of transferability is based on the performance drop observed when control software and/or design methods are ported from one platform to another. Results indicate that, while the control software generated via automatic design is possibly transferable, better performance can be achieved when a transferable method is directly applied to the new platform.
It has often been found that students appreciate hands-on work, and find that they learn more with courses that include a project than those relying solely on conventional lectures and tests. This type of project driv...
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It has often been found that students appreciate hands-on work, and find that they learn more with courses that include a project than those relying solely on conventional lectures and tests. This type of project driven learning is a key component of "Inquiry-based learning" (IBL), which aims at teaching methodology as well as content by incorporating the student as an actor rather than a spectator. robotics applications are especially well-suited for IBL due to the value of trial and error experience, the multiple possibilities for students to implement their own ideas, and the importance of programming, problem-solving, and electro-mechanical skills in real world engineering and science jobs. Furthermore, robotics platforms can be useful teaching media and learning tools for a variety of topics. Here, we present RoboGen: an open-source, web-based, software, and hardware platform for robotics and Artificial Intelligence with a particular focus on evolutionary robotics. We describe the platform in detail, compare it to existing alternatives, and present results of its use as a platform for Inquiry-based learning within a master's level course at the Ecole Polytechnique Federale de Lausanne.
Neuropsychological phenomena have been modelized mainly, by the mainstream approach, by attempting to reproduce their neural substrate whereas sensory-motor contingencies have attracted less attention. In this work, w...
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Neuropsychological phenomena have been modelized mainly, by the mainstream approach, by attempting to reproduce their neural substrate whereas sensory-motor contingencies have attracted less attention. In this work, we introduce a simulator based on the evolutionary robotics platform Evorobot* in order to setting up in silico neuropsychological tasks. Moreover, in this study we trained artificial embodied neurorobotic agents equipped with a pan/tilt camera, provided with different neural and motor capabilities, to solve a well-known neuropsychological test: the cancellation task in which an individual is asked to cancel target stimuli surrounded by distractors. Results showed that embodied agents provided with additional motor capabilities (a zooming/attentional actuator) outperformed simple pan/tilt agents, even those equipped with more complex neural controllers and that the zooming ability is exploited to correctly categorising presented stimuli. We conclude that since the sole neural computational power cannot explain the (artificial) cognition which emerged throughout the adaptive process, such kind of modelling approach can be fruitful in neuropsychological modelling where the importance of having a body is often neglected.
Walking control of biped robots is a challenging problem, and improving robustness to noise and uncertainty remains difficult. We recently developed a novel control framework for 3D bipedal walking that we call "...
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Walking control of biped robots is a challenging problem, and improving robustness to noise and uncertainty remains difficult. We recently developed a novel control framework for 3D bipedal walking that we call "linear reactive control." It is linear because control torques are computed as simple weighted sums of sensor states. It is reactive because it depends only on the model's current state. The present simulation study shows that this controller performs reliably in the presence of realistic models of joint actuation, sensor noise, and uncertainty in model and contact parameters. The controller is able to maintain a stable gait in the presence of noisy sensor inputs and low-impedance actuation. It also performs reliably on models with high uncertainty (up to 20%) in measurements of their dynamic parameters and widely varying ground contact parameters. The robustness of this controller to realistic conditions validates this method as a promising avenue for bipedal control.
We will discuss in which conditions we can expect the emergence of agents able to integrate sensory-motor information over time and later use this information to modulate their behavior accordingly. In doing so we wil...
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We will discuss in which conditions we can expect the emergence of agents able to integrate sensory-motor information over time and later use this information to modulate their behavior accordingly. In doing so we will illustrate the problems that these agents should be able to solve and the processes that might lead to a transition from simple agents that only rely on sensory information or on their internal dynamic to agents that are also able to integrate information over time. The analysis of evolved individuals revealed that: (1) individuals able to integrate information over time rely on mixed strategy in which basic sensory-motor mechanisms are complemented and enhanced with additional internal mechanisms;(2) evolved individuals tend to rely on partial, action-oriented, and action-mediated representations of the external environment.
This article depicts the approach used to build the Topos application, a simulation of two-wheel robots able to discern real complex sounds. Topos is framed in the nouvelle concept of subsymbolic artificial intelligen...
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This article depicts the approach used to build the Topos application, a simulation of two-wheel robots able to discern real complex sounds. Topos is framed in the nouvelle concept of subsymbolic artificial intelligence, applied to the field of evolutionary robotics. This paper focuses on the simulation of biologically inspired artificial cochleas and spiking neural networks, in order to model the embodied control system of the robots. The method chosen to find the most appropriate parameters that determine robots' behaviour is evolutionary computation techniques, with the aim of avoiding any human intervention in this task. As an example of a real application of this technique, experiments were performed to study the ability of the robots to distinguish sounds composed of parts of real canary songs and to navigate to the recognised signal. Results obtained confirm the validity of the approach. (c) 2007 Elsevier B.V. All rights reserved.
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