AI Game Development: Synthetic Creatures with Learning and Reactive Behaviors
| [A] [B] [C] [D] [E] [F] [G] [H] [I] [J] [K] [L] [M] [N] [O] [P] [Q] [R] [S] [T] [U] [V] [W] [X] Pacman 2nd Papert, Seymour Perceptrons parameterless genetic algorithms parameters actions 2nd genetic algorithms 2nd pathfinders pathfinding pattern recognition engineering 2nd patterns emergence perception emergent behaviors perception training training procedures perceptron weights 2nd 3rd perceptorns bias perceptrons 2nd 3rd 4th 5th 6th Perceptrons perceptrons Adaline (adaptive linear neurons) biologically inspired model 2nd dot products emotions feelings 2nd interfaces 2nd 3rd 4th 5th 6th moods portraying 2nd 3rd 4th 5th primary emotions 2nd sensations 2nd 3rd inputs 2nd 3rd 4th 5th 6th 7th linear approximation 2nd 3rd McCulloch, Warren and Walter Pitts MLPs (multilayer perceptrons) 2nd 3rd 4th 5th activation functions 2nd 3rd 4th 5th advantages biological parallels 2nd 3rd 4th 5th 6th 7th 8th connections 2nd data structures disadvantages generalization 2nd 3rd hidden units 2nd 3rd 4th incremental algorithms 2nd module design 2nd 3rd 4th simulation 2nd 3rd topologies 2nd 3rd training algorithms 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th 13th 14th 15th 16th validation 2nd MPLs target selection 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th 13th 14th 15th 16th 17th 18th 19th 20th optimization 2nd 3rd 4th brute-force optimization 2nd 3rd local minima 2nd 3rd momentum 2nd 3rd numeric optimization simulated annealing 2nd 3rd 4th steepest descent optimization 2nd 3rd 4th 5th 6th weights 2nd 3rd 4th 5th 6th 7th 8th outputs 2nd 3rd 4th 5th 6th 7th Rosenblatt, Frank 2nd simulation activation function 2nd 3rd net sums 2nd 3rd 4th outline 2nd weights training procedures 2nd 3rd 4th 5th 6th 7th 8th 9th perceptual sensations Perlin noise function personal objectives strategic decision making 2nd 3rd 4th phenetics 2nd phenomena (emergence) phenotype 2nd phenotype-specific operators phenotypes genotypes conversions 2nd 3rd 4th phylogenetic parts animats physical state prediction of movement 2nd 3rd physical states physics interfaces prediction of movement behaviors 2nd evaluation 2nd experimentation 2nd intersections 2nd 3rd numeric integration physical state 2nd 3rd simulation algorithm 2nd 3rd 4th 5th Picky animat Pitts, Walter Pizza Tycoon planning deliberative planning goal-oriented planning 2nd 3rd reactive planning compared 2nd 3rd 4th 5th 6th 7th 8th platforms fuzzy rules getting onto player state strategic decision making weapon selection 2nd player ststus 2nd point content functions point of collision finding policies behavior policies reinforcement learning 2nd 3rd evolutionary policies 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th 13th 14th 15th 16th 17th 18th 19th 20th 21st 22nd 23rd 24th 25th policy iteration algorithm 2nd 3rd polling Pong populations genetic algorithms 2nd 3rd postproduction stage development process practice importance of 2nd 3rd prediction of movement shooting behaviors 2nd evaluation 2nd experimentation 2nd intersections 2nd 3rd numeric integration physical state 2nd 3rd simulation algorithm 2nd 3rd 4th 5th predictions classifiers 2nd 3rd predictor variables data samples preditions shooting premature convergence genetic algorithms 2nd 3rd 4th preprocessing primary emotions 2nd designing primary terms primitive behaviors primitives Move primitive Turn primitive priority queues finite state machines probabilistic finite state automata probabilistic finite state machines probalistic state machines 2nd 3rd 4th 5th 6th 7th 8th 9th 10th problem solving engineering RBSs (rule-based systems) problems adaptive behaviors 2nd 3rd 4th 5th black box understanding informal knowledge 2nd software specification theoretical analysis 2nd 3rd 4th fundamental understanding nature 2nd 3rd properties 2nd 3rd 4th 5th methodology data analysis 2nd 3rd 4th 5th expert features 2nd feature identification 2nd refining decomposition 2nd 3rd simplification 2nd 3rd reinforcement learning exploitation 2nd 3rd exploration 2nd 3rd solutions complexity exhaustive expert guidance 2nd expert solutions hybrid approaches information theory 2nd instances minimal complexity 2nd 3rd 4th random representation 2nd 3rd 4th 5th search space 2nd 3rd 4th simulation algorithm tightness training underlying knowledge covariance 2nd 3rd 4th effective domains 2nd 3rd usage analysis 2nd 3rd variables 2nd 3rd 4th procedural finite state machines ambiguity 2nd code structure 2nd control flow 2nd data loss 2nd message passing 2nd redesigning sequential chaos 2nd procedures control logic finite state machines 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th learning systems programming adaptive behaviors AI 2nd 3rd dynamic programming reinforcement learning 2nd 3rd 4th 5th 6th 7th functional programming meta-programming practice importance of 2nd 3rd skill requirements programming languages programming stages development process projectiles dodging senses sketching tracking 2nd trajectories projections statistical analysis proof perceptron weights gradients 2nd properties search space 2nd 3rd weapon selection weapons 2nd learning 2nd 3rd scripting 2nd 3rd proposals weapon selection 2nd proprio-sensors prototypes functions pure decomposition purposeful movement pursuit steering behavior |