%0 Conference Paper %B Proc. 19th Annual Computational Neuroscience Meeting (CNS*2010) %D 2010 %T Evolution of Bistable Dynamics in Spiking Neural Controllers for Agents Performing Olfactory Attraction and Aversion %A Oros, Nicolas %A Volker Steuber %A Davey, Neil %A Lola Cañamero %A Roderick G Adams %B Proc. 19th Annual Computational Neuroscience Meeting (CNS*2010) %I BioMed Central Ltd. %C San Antonio, TX %V 11(Suppl 1) %P 92 %8 07/2010 %G eng %U http://bmcneurosci.biomedcentral.com/articles/10.1186/1471-2202-11-S1-P92 %R 10.1186/1471-2202-11-S1-P92 %0 Conference Paper %B Proc. 2009 IEEE Symposium on Artificial Life (ALIFE 2009) %D 2009 %T Evolution of Bilateral Symmetry in Agents Controlled by Spiking Neural Networks %A Oros, Nicolas %A Volker Steuber %A Davey, Neil %A Lola Cañamero %A Roderick G Adams %X We present in this paper three novel developmental models allowing information to be encoded in space and time, using spiking neurons placed on a 2D substrate. In two of these models, we introduce neural development that can use bilateral symmetry. We show that these models can create neural controllers for agents evolved to perform chemotaxis. Neural bilateral symmetry can be evolved and be beneficial for an agent. This work is the first, as far as we know, to present developmental models where spiking neurons are generated in space and where bilateral symmetry can be evolved and proved to be beneficial in this context. %B Proc. 2009 IEEE Symposium on Artificial Life (ALIFE 2009) %I IEEE Press %C Nashville, TN %P 116–123 %8 03/2009 %@ 978-1-4244-2763-5 %G eng %U http://ieeexplore.ieee.org/document/4937702/ %R 10.1109/ALIFE.2009.4937702 %0 Conference Paper %B Proc. 2009 IEEE Symposium on Artificial Life (ALIFE 2009) %D 2009 %T The role of lateral inhibition in the sensory processing in a simulated spiking neural controller for a robot %A David Bowes %A Roderick G Adams %A Lola Cañamero %A Volker Steuber %A Davey, Neil %X Visual adaptation is the process that allows animals to be able to see over a wide range of light levels. This is achieved partially by lateral inhibition in the retina which compensates for low/high light levels. Neural controllers which cause robots to turn away from or towards light tend to work in a limited range of light conditions. In real environments, the light conditions can vary greatly reducing the effectiveness of the robot. Our solution for a simple Braitenberg vehicle is to add a single inhibitory neuron which laterally inhibits the output to the robot motors. This solution has additionally reduced the computational complexity of our simple neuron allowing for a greater number of neurons to be simulated with a fixed set of resources. %B Proc. 2009 IEEE Symposium on Artificial Life (ALIFE 2009) %I IEEE %C Nashville, TN %P 179–183 %8 03/2009 %@ 978-1-4244-2763-5 %G eng %U http://ieeexplore.ieee.org/document/4937710/ %R 10.1109/ALIFE.2009.4937710 %0 Conference Paper %B Proc. 9th International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems (EpiRob 2009) %D 2009 %T Should I worry about my stressed pregnant robot? %A David Bowes %A Lola Cañamero %A Roderick G Adams %A Volker Steuber %A Davey, Neil %E Lola Cañamero %E Pierre-Yves Oudeyer %E Christian Balkenius %B Proc. 9th International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems (EpiRob 2009) %S Lund University Cognitive Studies %I Lund University %C Venice, Italy %V 146 %P 203–204 %8 11/2009 %@ 978-91-977-380-7-1 %G eng %U http://www.lucs.lu.se/LUCS/146/epirob09.pdf %0 Conference Paper %B From Animals to Animats 10: Proc. 10th International Conference on Simulation of Adaptive Behavior (SAB 2008) %D 2008 %T Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks %A Oros, Nicolas %A Volker Steuber %A Davey, Neil %A Lola Cañamero %A Roderick G Adams %E Asada, Minoru %E Hallam, John C T %E Jean-Arcady Meyer %E Tani, Jun %X We created a neural architecture that can use two different types of information encoding strategies depending on the environment. The goal of this research was to create a simulated agent that could react to two different overlapping chemicals having varying concentrations. The neural network controls the agent by encoding its sensory information as temporal coincidences in a low concentration environment, and as firing rates at high concentration. With such an architecture, we could study synchronization of firing in a simple manner and see its effect on the agent’s behaviour. %B From Animals to Animats 10: Proc. 10th International Conference on Simulation of Adaptive Behavior (SAB 2008) %S Lecture Notes in Computer Science (LNCS) %I Springer, Berlin, Heidelberg %C Osaka, Japan %V 5040 %P 148–158 %8 07/2008 %@ 978-3-540-69134-1 %G eng %U http://link.springer.com/chapter/10.1007/978-3-540-69134-1_15 %R 10.1007/978-3-540-69134-1_15 %0 Conference Paper %B Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems %D 2008 %T Optimal Noise in Spiking Neural Networks for the Detection of Chemicals by Simulated Agents %A Oros, Nicolas %A Volker Steuber %A Davey, Neil %A Lola Cañamero %A Roderick G Adams %E Seth Bullock %E Jason Noble %E Richard A. Watson %E Mark A Bedau %X We created a spiking neural controller for an agent that could use two different types of information encoding strategies depending on the level of chemical concentration present in the environment. The first goal of this research was to create a simulated agent that could react and stay within a region where there were two different overlapping chemicals having uniform concentrations. The agent was controlled by a spiking neural network that encoded sensory information using temporal coincidence of incoming spikes when the level of chemical concentration was low, and as firing rates at high level of concentration. With this architecture, we could study synchronization of firing in a simple manner and see its effect on the agent’s behaviour. The next experiment we did was to use a more realistic model by having an environment composed of concentration gradients and by adding input current noise to all neurons. We used a realistic model of diffusive noise and showed that it could improve the agent’s behaviour if used within a certain range. Therefore, an agent with neuronal noise was better able to stay within the chemical concentration than an agent without. %B Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems %I MIT Press %C Winchester, UK %P 443–449 %8 08/2008 %@ 978-0-262-75017-2 %G eng %U https://mitpress-request.mit.edu/sites/default/files/titles/alife/0262287196chap58.pdf %0 Conference Paper %B Proc. 9th European Meeting on Cybernetics and Systems Research, Vol. II %D 2008 %T Optimal Receptor Response Functions for the Detection of Pheromones by Agents Driven by Spiking Neural Networks %A Oros, Nicolas %A Volker Steuber %A Davey, Neil %A Lola Cañamero %A Roderick G Adams %E Trappl, R %X The goal of the work presented here is to find a model of a spiking sensory neuron that could cope with small variations in the concentration of simulated chemicals and also the whole range of concentrations. By using a biologically plausible sigmoid function in our model to map chemical concentration to current, we could produce agents able to detect the whole range of concentration of chemicals (pheromones) present in the environment as well as small variations of them. The sensory neurons used in our model are able to encode the stimulus intensity into appropriate firing rates. %B Proc. 9th European Meeting on Cybernetics and Systems Research, Vol. II %I Austrian Society for Cybernetic Studies %C Vienna, Austria %P 427–432 %8 03/2008 %@ 978-3-85206-175-7 %G eng %U http://www.cogsci.uci.edu/~noros/mypapers/OROS_2008_EMCSR.pdf %0 Conference Paper %B Proc. 4th International Workshop on Artificial Neural Networks and Intelligent Information Processing (ANNIIP 2008) %D 2008 %T Receptor Response and Soma Leakiness in a Simulated Spiking Neural Controller for a Robot %A David Bowes %A Roderick G Adams %A Lola Cañamero %A Volker Steuber %A Davey, Neil %E Madani, K %X This paper investigates different models of leakiness for the soma of a simulated spiking neural controller for a robot exhibiting negative photo-taxis. It also investigates two models of receptor response to stimulus levels. The results show that exponential decay of ions across the soma and of a receptor response function where intensity is proportional to intensity is the best combination for dark seeking behaviour. %B Proc. 4th International Workshop on Artificial Neural Networks and Intelligent Information Processing (ANNIIP 2008) %I INSTICC (Inst. Syst. Technologies Information Control and Communication) %C Funchal, Madeira, Portugal %P 100–106 %8 05/2008 %@ 978-989-8111-33-3 %G eng %U https://uhra.herts.ac.uk/handle/2299/6832