Index
A
- A*
- extending, for coordination / Extending A* for coordination: A*mbush, How to do it…, How it works…
- A* algorithm
- used, for finding best promising path / Finding the best-promising path with A*, Getting ready, How to do it..., There's more...
- improving, for memory / Improving A* for memory: IDA*, How to do it…, How it works…
- A*mbush algorithm
- AB Negamaxing
- about / AB Negamaxing, How to do it…, How it works…
- actions
- predicting, with N-Gram predictor / Predicting actions with an N-Gram predictor, Getting ready…, How to do it…, How it works…
- agents
- avoiding / Avoiding agents, How to do it..., There's more
- air-hockey rival
- building / Building an air-hockey rival, Getting ready, How to do it…, How it works…
- arriving
- about / Arriving and leaving, How to do it...
- artificial neural networks
- awareness
- creating, in stealth game / Creating awareness in a stealth game, Getting ready, How to do it…, How it works…, There is more…
B
- behaviors
- template, creating / Creating the behavior template, How to do it..., See also
- blending, by weight / Blending behaviors by weight, How to do it...
- blending, by priority / Blending behaviors by priority, Getting ready, How to do it..., How it works...
- combining, steering pipeline used / Combining behaviors using a steering pipeline, Getting ready, How to do it..., How it works...
- behavior trees
- implementing / Implementing behavior trees, How to do it..., How it works...
- Breadth-First Search (BFS) algorithm
- used, for finding shortest path in grid / Finding the shortest path in a grid with BFS, How to do it..., How it works...
C
- checkers
- rival, implementing / Implementing a checkers rival, How to do it…, How it works…
- collider-based system
- used, for seeing function / The seeing function using a collider-based system, How to do it…
- used, for hearing function / The hearing function using a collider-based system, How to do it…, There is more…
- used, for smelling function / The smelling function using a collider-based system, How to do it…, There is more…
- constraints / There's more...
- convolution filters
- used, for improving influence / Improving influence with convolution filters, How it works…, There is more…
D
- decisions
- making / Introduction
- making, with goal-oriented behaviors / Making decisions with goal-oriented behaviors, How to do it..., How it works...
- decision tree
- selecting through / Choosing through a decision tree, How to do it..., There's more...
- and finite-state machines (FSM) / Combining FSMs and decision trees, How to do it..., How it works...
- using / Learning to use decision trees, How to do it…
- decomposers / There's more...
- Depth-First Search (DFS) algorithm
- used, for finding way out of maze / Finding your way out of a maze with DFS, How to do it..., There is more…
- Dijkstra algorithm
- used, for finding shortest path / Finding the shortest path with Dijkstra, How to do it..., There's more...
- Dirichlet domains
- used, for representing world / Representing the world with Dirichlet domains
E
- editors
- URL / There's more...
- emergent particles
- creating, harmony search used / Creating emergent particles using a harmony search, How to do it…, How it works…
- evading behavior
F
- fighting circle
- building / Building a fighting circle, Getting ready, How to do it…, How it works…
- finite-state machines (FSM)
- working / Working a finite-state machine, How to do it..., There's more...
- hierarchical / Improving FSMs: hierarchical finite-state machines
- improving / Improving FSMs: hierarchical finite-state machines, How to do it..., How it works...
- and decision trees, combining / Combining FSMs and decision trees, How to do it..., How it works...
- formations
- handling / Handling formations, Getting ready, How to do it…, There is more…
- fuzzy logic
- working with / Working with fuzzy logic, How to do it..., How it works...
G
- game-tree class
- working with / Working with the game-tree class, How to do it…
- Game Programming Wiki (GPWiki)
- URL / Getting ready
- goal-oriented behaviors
- decisions, making with / Making decisions with goal-oriented behaviors, How to do it..., How it works...
- graph-based system
- used, for seeing function / The seeing function using a graph-based system, How to do it…, How it works…
- used, for hearing function / The hearing function using a graph-based system, How to do it…, How it works…, See also
- used, for smelling function / The smelling function using a graph-based system, How to do it…
- grids
- used, for representing world / Representing the world with grids, Getting ready, How to do it..., How it works..., There's more...
- shortest path finding, BFS used / Finding the shortest path in a grid with BFS, How to do it..., How it works...
H
- harmony search
- used, for creating emergent particles / Creating emergent particles using a harmony search, How to do it…, How it works…
- hearing function
- collider-based system used / The hearing function using a collider-based system, How to do it…, There is more…
- graph-based system used / The hearing function using a graph-based system, How to do it…
I
- IDA* / Improving A* for memory: IDA*, How to do it…
- influence
- improving, map flooding used / Improving influence with map flooding, Getting ready, How to do it…, How it works…
- improving, convolution filters used / Improving influence with convolution filters, How to do it…, How it works…, See also
- influence maps
- about / Influence maps, How to do it…, How it works…
J
- jump system
- creating / Creating a jump system
L
- leaving
- about / Arriving and leaving, How to do it...
M
- map flooding
- used, for improving influence / Improving influence with map flooding, Getting ready, How to do it…, How it works…
- maps
- URL / See also
- Markov system / Representing states with numerical values: Markov system, How to do it..., How it works...
- mazes
- creating, procedurally / Creating mazes procedurally, How to do it…
- Minimax
N
- N-Gram predictor
- used, for predicting actions / Predicting actions with an N-Gram predictor, Getting ready…, How to do it…, How it works…
- improving / Improving the predictor: Hierarchical N-Gram, How to do it…, How it works…
- navigation
- planning, in several frames / Planning navigation in several frames: time-sliced search, How to do it...
- Naïve Bayes classifier
- Negamaxing
- about / Negamaxing, How to do it…, See also
- Negascouting
- about / Negascouting, How to do it…, How it works…
O
- object pool pattern
- URL / See also
- objects
- facing / Facing objects, How to do it...
P
- path
- following / Following a path, How to do it..., How it works..., There's more...
- smoothing / Smoothing a path, How to do it…, How it works…
- points of visibility
- used, for representing world / Representing the world with points of visibility, How to do it..., How it works..., See also
- projectile
- shooting / Shooting a projectile, There's more...
- landing spot, predicting / Predicting a projectile's landing spot, How to do it...
- targeting / Targeting a projectile, How it works...
- pursuing behavior
R
- race difficulty
- managing, rubber-banding system used / Managing race difficulty using a rubber-banding system, Getting ready, How to do it...
- random numbers
- handling / Handling random numbers better, Getting ready, How to do it…, See also
- RaycastHit structure
- URL / See also
- reinforcement
- rubber-banding system
- used, for managing race difficulty / Managing race difficulty using a rubber-banding system, Getting ready, How to do it...
S
- search window / Negascouting
- seeing function
- using, collider-based system used / The seeing function using a collider-based system, How to do it…
- graph-based system used / The seeing function using a graph-based system, How to do it…, How it works…
- self-driving car
- implementing / Implementing a self-driving car
- self-made navigation mesh
- used, for representing world / Representing the world with a self-made navigation mesh
- shortest path
- finding, Dijkstra used / Finding the shortest path with Dijkstra, How to do it..., There's more...
- smelling function
- collider-based system used / The smelling function using a collider-based system, How to do it…, How it works…
- graph-based system used / The smelling function using a graph-based system, How to do it…
- states
- representing, with numerical values / Representing states with numerical values: Markov system, How to do it..., How it works...
- stealth game
- awareness, creating / Creating awareness in a stealth game, Getting ready, How to do it…, How it works…, There is more…
T
- table-football competitor
- devising / Devising a table-football competitor, How to do it…
- targeters / There's more...
- tic-tac-toe
- rival, implementing / Implementing a tic-tac-toe rival, How to do it…
- time-sliced search
U
- Unity game loop
- URL / See also
W
- walls
- avoiding / Avoiding walls, How to do it..., See also
- wander behavior
- about / Wandering around, How to do it..., How it works...
- waypoints
- creating / Creating good waypoints, How to do it…
- analyzing, by height / Analyzing waypoints by height, How it works…
- analyzing, by cover and visibility / Analyzing waypoints by cover and visibility, How to do it…
- exemplifying, for decision making / Exemplifying waypoints for decision making, How it works…
- world
- representing, grids used / Representing the world with grids, Getting ready, How to do it..., How it works..., There's more...
- representing, Dirichlet domains used / Representing the world with Dirichlet domains, Getting ready, How to do it..., There's more...
- representing, points of visibility used / Representing the world with points of visibility, How to do it..., See also
- representing, self-made navigation mesh used / Representing the world with a self-made navigation mesh, How to do it...