The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011, La Palma, Canary Islands, Spain, May 30 - June 3, 2011. Proceedings, Part I
Cognitive functions such as a perception, thinking and acting are based on the working of the brain, one of the most complex systems we know. The traditional scientific methodology, however, has proved to be not sufficient to understand the relation between brain and cognition. The aim of this paper is to review an alternative methodology – nonlinear dynamical analysis – and to demonstrate its benefit...
In conditional learning, one investigates the computational principles by which the human brain solves challenging recognition problems. The role of temporal context in the learning of arbitrary visuo-motor associations has so far been studied mostly in primates. We model the explicit learning task where a sequence of visual objects is presented to human subjects. The computational modelling of the...
Nowadays science has not found a way to unify the behavior of biological and autonomous nonbiological systems. While psychology uses the property of intelligence as a basis for explaining cognitive behaviors, artificial intelligence has been unable to explain that property and provide to nonbiological systems with it. In addition, discoveries in the last decade have demonstrated the existence of random...
This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-election of heterogeneous specialized tasks by autonomous robots, as opposed to the usual multi-tasks allocation problem in multi-robot systems in which an external controller distributes the existing tasks among the individual robots. We are rather interested on decentralized solutions...
We present an incremental model of lexicon consensus in a population of simulated agents. The emergent lexicon is evolved with a hybrid algorithm which is based on grammatical evolution with semantic rules and reinforcement learning. The incremental model allows to add subsequently new agents and objects to the environment when a consensual language has emerged for a steady set of agents and objects...
We are interested in the next generation of industrial robots, those that are able to operate in dynamic and unstructured environments and, consequently, that are able to adapt to changing circumstances or to work on different tasks in an autonomous way. In this sense, multirobot systems and, in particular, modular systems present several features like scalability, fault tolerance, low maintenance...
This paper proposes the EvoBANE system. EvoBANE automatically generates Bayesian networks for solving special-purpose problems. EvoBANE evolves a population of individuals that codify Bayesian networks until it finds near optimal individual that solves a given classification problem. EvoBANE has the flexibility to modify the constraints that condition the solution search space, self-adapting to the...
In this paper we propose a novel data clustering algorithm based on the idea of considering the individual data items as cells belonging to an uni-dimensional cellular automaton. Our proposed algorithm combines insights from both social segregation models based on Cellular Automata Theory, where the data items themselves are able to move autonomously in lattices, and also from Ants Clustering algorithms,...
In this paper, the presynaptic rule, a classical rule for hebbian learning, is revisited. It is shown that the presynaptic rule exhibits relevant synaptic properties like synaptic directionality, and LTP metaplasticity (long-term potentiation threshold metaplasticity). With slight modifications, the presynaptic model also exhibits metaplasticity of the long-term depression threshold, being also consistent...
Sets of coupled neurons can generate many different patterns in response to modulatory or sensory inputs. The study of how these patterns have been generated from the inputs has been object of great interest in the literature. These studies have been mainly performed by means of computer simulations, based on differential models or phenomenological models. However complete descriptions of the behaviour...
The balance between inhibition and excitation is at the basis of the maintenance of stable and normal brain electrical activity. Experimental results revealed that inhibitory synapses can become depolarizing as the intracellular concentration of Cl− 1 of the postsynaptic cells increases. In this work the dynamical behaviour of a network of pyramidal cells coupled to inhibitory Fast-Spiking...
Early motor organization using the Domans inclined floor method is simulated with a four neurons robot. A LEGO robot controlled by a biologically plausible neural network performs the same kind of “inclined floor” training that is given by parents to young babies for early motor organization. When the inclined floor training is applied to the robot, it organizes its motor behavior in a manner that...
The training algorithm studied in this paper is inspired by the biological metaplasticity property of neurons. Tested on different multidisciplinary applications, it achieves a more efficient training and improves Artificial Neural Network Performance. The algorithm has been recently proposed for Artificial Neural Networks in general, although for the purpose of discussing its biological plausibility,...
In the present work we propose a dynamic model of the lateral geniculate nucleus (dLGN) that allows the implementation of different configurations of the push-pull circuitry in order to study the spatio-temporal filtering being carried out. It is widely accepted that each relay neuron receives only one input from a single retinal ganglion cell, which leads to interpret that the thalamus preserves...
This paper deals with the problem of obtaining coordinated behavior in multirobot systems by evolution. More specifically, we are interested in using a method that allows the emergence of different species if they are required by the task, that is, if specialization provides an advantage in the completion of the task, without the designer having to predefine the best way to solve it. To this end,...
Applying conventional Q-Learning to Multi-Component Robotic Systems (MCRS) increasing the number of components produces an exponential growth of state storage requirements. Modular approaches limit the state size growth to be polynomial on the number of components, allowing more manageable state representation and manipulation. In this article, we advance on previous works on a modular Q-learning...
In Multi-agent systems, the study of language and communication is an active field of research. In this paper we present the application of Reinforcement Learning (RL) to the self-emergence of a common lexicon in robot teams. By modeling the vocabulary or lexicon of each agent as an association matrix or look-up table that maps the meanings (i.e. the objects encountered by the robots or the states...
In this paper, we present a multi-agent system for easy and quick robot deployment of robots in different environments, without prior software development and without the need of maps of the environment where the robot will work. Our system, consisting on a network of intelligent cameras and autonomous robots, is able to manage local interactions amongst the intelligent cameras spread across the environment,...
In the inspection of a known environment by a team of robots, communication problems may exists between members of the team, even, due to the hostile environment these members can be damaged. In this paper, a redundant, robust and fault tolerant method to cover a known environment using a multi-agent system and where the communications are not guaranteed is presented. Through a simple auction system...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.