Figure 5.5: The sigmoid (squashing) activation function.
Figure 5.6: Hidden and output layers of a sample neural network.
Figure 5.7: Numerical backpropagation example.
Figure 5.8: Example of a neurocontroller in an environment.
Figure 5.9: Winner-take-all group .
Figure 5.10: Game AI neurocontroller architecture for verification.
Figure 5.11: Sample run of the backpropagation algorithm on the neurocontroller.
Chapter 6: Introduction to Genetic Algorithms
Figure 6.1: Encoding candidate solutions into chromosomes.
Figure 6.2: Genetic algorithm high-level flow.
Figure 6.3: Initialization of the genetic pool.
Figure 6.4: Evaluation of the population.
Figure 6.5: Selecting chromosomes based upon their fitness.
Figure 6.6: Recombining chromosomes for a new population.
Figure 6.7: Single and multi-point crossover.
Figure 6.8: Mutating a single chromosome.
Figure 6.9: Graphical plot of Equation 6.1.
Figure 6.10: Contour plot of Equation 6.1 showing z-dimension via shading.
Figure 6.11: Initial population (t ).
Figure 6.12: Fitness of initial population.
Figure 6.13: Next generation with fitness evaluated (population at t 1 ).
Figure 6.14: Plot of fitness over time in evolving for Equation 6.5.
Chapter 7: Artificial Life
Figure 7.1: Simple food chain.
Figure 7.2: Toroid grid world for the food chain simulation.
Figure 7.3: Agent systems model.
Figure 7.4: Agent's area of perception ( facing north).
Figure 7.5: Winner-takes-all neural network as the agent brain.
Figure 7.6: Neural network for evolved herbivore.
Figure 7.7: Herbivore at time t .
Figure 7.8: Herbivore at time T 1 .
Figure 7.9: Herbivore at time T 2 .
Figure 7.10: Age progression in a sample simulation.
Figure 7.11: Run-time trend data from a playback simulation. Herbivore and carnivore births, while represented in the graph, are not visible due to the graph scaling and frequency of the herbivore and carnivore deaths.
Chapter 8: Introduction to Rules-Based Systems
Figure 8.1: Rules-based system illustration.
Figure 8.2: Rules-based system phases.
Figure 8.3: Graphical depiction of a blackboard architecture.
Figure 8.4: Basic flow of the rules-based system.
Figure 8.5: Format of rules within the system.
Chapter 9: Introduction to Fuzzy Logic
Figure 9.1: Quality of service scenario with rate feedback.
Figure 9.2: Membership function for packet rate.
Figure 9.3: Predator membership functions.
Figure 9.4: Predatory/prey example plot.
Figure 9.5: The fuzzy logic axioms.
Figure 9.6: Fuzzy voltage membership graph.
Figure 9.7: Fuzzy temperature membership graph.
Figure 9.8: Charge curves for the battery charge control simulation.
Chapter 10: The Bigram Model
Figure 10.1: Example Markov Chain.
Figure 10.2: Learning user interaction with an email program.