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] Kanga animat knowledge learning systems knowledge base fuzzy set theory 2nd 3rd knowledge elicitation RBSs (rule-based systems) 2nd 3rd 4th 5th knowledge engineer approach membership functions creating knowledge of the problem black box understanding informal knowledge 2nd software specification theoretical analysis 2nd 3rd 4th fundamental understanding nature 2nd 3rd properties 2nd 3rd 4th 5th information theory 2nd methodology data analysis 2nd 3rd 4th 5th expert features 2nd feature identification 2nd minimal complexity 2nd 3rd 4th refining decomposition 2nd 3rd simplification 2nd 3rd representation 2nd 3rd 4th search space properties 2nd 3rd solutions exhaustive expert guidance 2nd expert solutions hybrid approaches random underlying knowledge covariance 2nd 3rd 4th effective domains 2nd 3rd usage analysis 2nd 3rd variables 2nd 3rd 4th knowledge represeantation RBSs (rule-based systems) 2nd 3rd knowledge representation (KR) 2nd 3rd [See KR (knowledge representation)] KR (knowledge representation) 2nd formalisms 2nd frames introspection 2nd object-attribute-value paradigm 2nd semantic networks 2nd 3rd symbols 2nd |