Intelligence as adaptive behavior: an experiment in computational neuroethology
Intelligence as adaptive behavior: an experiment in computational neuroethology
A concurrent object-oriented framework for the simulation of neural networks
OOPSLA/ECOOP '90 Proceedings of the workshop on Object-based concurrent programming
The roots of backpropagation: from ordered derivatives to neural networks and political forecasting
The roots of backpropagation: from ordered derivatives to neural networks and political forecasting
Communication in reactive multiagent robotic systems
Autonomous Robots
Adaptive Behavior - Special issue on computational neuroethology
The NEURON simulation environment
Neural Computation
Using emergent modularity to develop control systems for mobile robots
Adaptive Behavior - Special issue on environment structure and behavior
The book of GENESIS (2nd ed.): exploring realistic neural models with the GEneral NEural SImulation System
Embedding robots into the Internet
Communications of the ACM
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
The Neural Simulation Language: A System for Brain Modeling
The Neural Simulation Language: A System for Brain Modeling
Ecological Robotics: A Schema-Theoretic Approach
Intelligent Robots: Sensing, Modeling and Planning [Dagstuhl Workshop, September 1-6, 1996]
Comparative Experimental Studies on Spatial Memory and Learning in Rats and Robots
Journal of Intelligent and Robotic Systems
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Biology has been an important source of inspiration in building adaptive autonomous robotic systems. Due to the inherent complexity of these models, most biologically-inspired robotic systems tend to be ethological without linkage to underlying neural circuitry. Yet, neural mechanisms are crucial in modelling adaptation and learning. The work presented in this paper describes a schema and neural network multi-level modelling approach to biologically inspired autonomous robotic systems. A prey acquisition model with detour behaviour in frogs is presented to exemplify the modelling approach. The model is tested with simulated and physical robots using the ASL/NSL and MIRO robotic system.