A type of best-first search strategy which attempts to expand the node with the lowest estimated total
cost from the root, through the node, to a goal state.
A function which examines a game state at a particular depth, and returns true
if a HeuristicStateEvaluationFunction, rather than deeper alpha-beta search
should be used to evaluate the state.
Array of the eight compass directions (the single-step vector in each direction),
in clockwise order (North, Northeast, East, Southwest, South, Southwest, West, Northwest).
A minimax function that applies a cutoff test to states; for these states,
rather than continuing the minimax search, it applies a HeuristicStateEvaluationFunction.
Percept received just once, at the beginning of the game, indicating the basic setup of this game instance --
the size of the board, the operating rules, how many players there are, and which turn # your agent is assigned.
Runs repeated rounds of the Roomba environment,
noting the number of steps the robot needed to finish (if it finished),
the competitive ratio, the amount of time used per step,
and the averages of those figures at the end.
Standard -
Static variable in class edu.columbia.cs.coms4701.agent.environments.pente.PenteRules
Standard rules:
* 19x19 board,
* 5-in-a-row to win,
* 10 captured stones (5 pairs) to win,
* Black must begin in center,
* Black's second move must be at least 2 spaces away from the center
Standard rules, but on a smaller 13x13 board:
* 13x13 board,
* 5-in-a-row to win,
* 10 captured stones (5 pairs) to win,
* Black must begin in center,
* Black's second move must be at least 2 spaces away from the center
Given a particular state x, returns a set of (action, successor) ordered pairs,
where each action is one of the legal actions in state x and each successor
is a state that can be reached from x by applying the action.
Given a particular state x, returns a set of (action, successor) ordered pairs,
where each action is one of the legal actions in state x and each successor
is a state that can be reached from x by applying the action.