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I have now finished work on a much more advanced version of the insect simulator named AnimatLab. AnimatLab is a software tool that combines biomechanical simulation and biologically realistic neural networks. You can build the body of an animal, robot, or other machine and place it in a virtual 3-D world where the physics of its interaction with the environment are accurate and realistic. You can then design a nervous system that controls the behavior of the body in the environment. The software currently has support for simple firing rate neuron models and leaky integrate and fire spiking neural models. In addition, there a number of different synapse model types that can be used to connect the various neural models to produce your nervous system. On the biomechanics side there is support for a variety of different rigid body types, including custom meshes that can be made to match skeletal structures exactly. The biomechanics system also has hill-based muscle and muscle spindle models. These muscle models allow the nervous system to produce movements around joints. In addition, there are also motorized joints for those interested in controlling robots or other biomimetic machines. This allows the user to generate incredibly complicated artificial lifeforms that are based on real biological systems. Best of all AnimatLab is completely free and it includes free C++ source code!

4.0 2D Insect Simulator

1. Simulation Purpose

The 2D insect is the latest step in my overall research. The goal of this project is to reproduce the work done by Dr. Randall Beer to produce a virtual insect that is completely controlled by a neural network, and that can survive for an indefinite amount of time in an environment with numerous obstacles and some food. No behavior will be explicitly programmed into this simulated insect. In other words, nowhere in the simulation code will there be a line that says "if the food is to the right of you then turn right." Everything the insect does results solely from the dynamic interactions between the different neurons in its brain. These neurons detect things from the environment like odor from food, and they move the parts of the insect's body like its legs and mouth. It is up to this network of neurons to produce the correct timing and synchronization required to produce behavior that will allow the insect to remain alive. In order to stay alive the insect must be able to navigate its way around its environment so that it can find and eat food. If it does not eat, then it will die.

2. Section Overview

The first part of this section is a discussion on how to model a neuron, and the different types of neurons and synapses that are used in this simulation. Then there is a brief description of the simulated insect and its environment. After that the discussion moves on to talk about the difficulties involved in walking and how the neural net solves the problem. After that is a description of how the insect explores its environment. Then there is section on how the insect finds and eats food, and how it dies. Finally, the last topic of this section shows the results of several different long-term runs of this simulated system.

 4.2D Insect Simulator
  4.1Modeling The Neuron
   4.1.1Neuron Basics
   4.1.2Neuron Model
   4.1.3Numerical Integration
   4.1.4Regular Neuron
   4.1.5Pacemaker Neuron
   4.1.6Sensory Neuron
   4.1.7Motor Neuron
   4.1.8Random Neuron
  4.2Virtual 2D World
   4.3.1Insect Locomotion
   4.3.2Leg Controller
   4.3.3Locomotion Controller
   4.4.2Edge Following
   4.4.3Obstacle Avoidance
   4.5.1Appetitive Controller
   4.5.4Food Vulture

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