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] back propagation MLPs (multilayer perceptrons) 2nd 3rd 4th 5th 6th 7th 8th backups reinforcement learning 2nd 3rd backward connections backward-chain interpreters hypothesize-test cycles backward-chaining interpreters RBS interpreters 2nd 3rd bagging DTs (decision trees) 2nd ballistics shooting batch algorithms MLPs (multilayer perceptrons) 2nd batch learning batching embodied agents behavior policies reinforcement learning 2nd 3rd behavioral decomposition behaviors adaptive behaviors AI engineering debugging 2nd design 2nd 3rd 4th methodologies 2nd problems 2nd 3rd 4th 5th programming testing 2nd adaptive gathering behaviors reinforcement learning 2nd 3rd architectures emergent behaviors 2nd 3rd 4th 5th affordance 2nd broadcasting environments 2nd functionality 2nd 3rd perception evaluation 2nd 3rd learning behaviors imitation shaping training trial and error learning systems movement fuzzy set theory 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th 13th 14th 15th 16th 17th 18th 19th 20th 21st objects collecting contraptions 2nd 3rd criteria 2nd 3rd specification 2nd 3rd 4th 5th 6th 7th prediction of movement 2nd responses designing steering behaviors assumptions 2nd fleeing 2nd 3rd forced exploration obstacle avoidance 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th obstacle avoidance algorithm projecting targets seeking 2nd 3rd wandering subsumption architecture 2nd 3rd 4th 5th 6th tactical behaviors capability customization 2nd 3rd 4th 5th strategic decision making 2nd subsumption architecture 2nd 3rd 4th 5th wall-following behaviors 2nd 3rd believability AI importance of bias perceptrons binary strings classifiers biological evolution defensive actions application 2nd 3rd 4th 5th evolutionary outline 2nd fitness computations 2nd 3rd genetic operators 2nd 3rd 4th module design 2nd 3rd 4th representation 2nd 3rd 4th 5th 6th emotions 2nd AI techniques 2nd biological models 2nd human/machine interaction 2nd 3rd 4th genomics 2nd 3rd 4th phenetics 2nd reproduction 2nd 3rd theory of evolution 2nd 3rd biological parallels MLPs (multilayer perceptrons) 2nd brains 2nd 3rd neurons 2nd 3rd biologically inspired models neural networks 2nd Black & White black box understanding informal knowledge 2nd software specification theoretical analysis 2nd 3rd 4th bodies classifiers Boltzmann distribution Boolean conditional test DTs (decision trees) boosting DTs (decision trees) 2nd bootstrapping reinforcement learning 2nd bottom-up design brains perceptrons 2nd 3rd branches DTs pruning 2nd 3rd DTs (decision trees) broadcasting emergent behaviors Brooks, Rodney brute-force optimization perceptrons 2nd 3rd |