What we have covered so far
Chapters Introduction, 1, 2, 3, 4, 5, 6, beginning of 7

Introduction
distinction between Academic AI and Game AI
types of play: turn-based, semi-real-time, simultaneous action,
real-time

Chapter 1
2D vectors, length, normalized, dot product, angle between vectors
determining when a point is above or below a plane
having a location and an orientation; 2.5D representation
physics: time, distance, mass
behavior: position, velocity, acceleration, force.
Euler integration to get  velocity from acceleration, position from
velocity
force (= m*a)

Chapter 2
Finite state machines
Switch statement implementation
state objects; execute method, ChangeState method, CurrentState
variable
Update method for everything
Enter, Exit actions
StateMachine as a separate object
Message passing
telegrams
EntityManager (HashMap)
MessageDispatcher; Discharge, DispatchMessage, DispatchDelayedMessages
HandleMessage, OnMessage
GlobalState

Chapter 3
Autonomous movement: action selection, steering, locomotion
MovingEntity: Velocity, Heading, Side, Mass, MaxSpeed, MaxForce,
MaxTurnRate, boundingRadius, Position, Scale
Vehicle class: World, Steering, timeElapsed
Steering behaviors: Seek, Flee, Arrive, Pursuit, Evade, wander,
obstacle Avoidance, Wall Avoidance (feelers), Interpose, Hide,
Path following, Offset Pursuit
Group Behaviors
neighbors
Separation, Alignment, Cohesion (Flocking)
Combining steering forces
Cell-space Partitioning
Smoothing

Chapter 4
simple soccer: soccer pitch, goals, ball, teams, goalkeeper,Field
players
regions
frictional force
TimeToCoverDistance
ReceivingPlayer
PlayerClosestToBall
ControllingPlayer
SupportingPlayer
Team states: PrepareForKickOff, Defending, Attacking
Field player states: GlobalPlayerState, ChaseBall, Wait,
ReceiveBall, KickBall, Dribble, SupportAttacker, ReturnToHomeRegion
Goal Keeper states: GlobalKeeperState, TendGoal, ReturnHome,
PutBallBackInPlay, InterceptBall
Key methods and tests
isPassSafeFromOpponent, CanShoot, findPass, GetBestPassToReceiver
Why approximations and estimations are good things.

Chapter 5
Graphs, nodes, edges, adjacency lists
Search algorithms
depth first search - frontier of nodes in a stack
breath first search - frontier of nodes in a queue
iterative deepening
Dijkstra's algorithm
A* algorithm
for pathfinding, common heuristic functions are
Euclidian distance, Manhatten distance, Chebyshev distance, octile
distance, linear approximation to Euclidian distance
Fast pathfinding algorithm that follows walls
Alternatives to square grids: hexagonal, triangular
Simulated hexagonal

Chapter 6

Scripts, scripting languages
comments, variables, multiple assignment, types
conditional structures: if, while, repeat, for