Module `pacai.agents.search.corners`

Expand source code

from pacai.agents.search.base import SearchAgent
from pacai.core.search import search
from pacai.student import searchAgents

class AStarCornersAgent(SearchAgent):
    """
    A search agent for `pacai.student.searchAgents.CornersProblem` using A*
    and `pacai.student.searchAgents.cornersHeuristic`.
    """

    def __init__(self, index, **kwargs):
        super().__init__(index, **kwargs)

        self.searchFunction = lambda prob: search.astar(prob, searchAgents.cornersHeuristic)
        self.searchType = searchAgents.CornersProblem

Classes

class AStarCornersAgent (index, **kwargs)

A search agent for CornersProblem using A* and cornersHeuristic().

Expand source code

class AStarCornersAgent(SearchAgent):
    """
    A search agent for `pacai.student.searchAgents.CornersProblem` using A*
    and `pacai.student.searchAgents.cornersHeuristic`.
    """

    def __init__(self, index, **kwargs):
        super().__init__(index, **kwargs)

        self.searchFunction = lambda prob: search.astar(prob, searchAgents.cornersHeuristic)
        self.searchType = searchAgents.CornersProblem

Ancestors

Static methods

def loadAgent(name, index, args={}): Inherited from: SearchAgent.loadAgent

Load an agent with the given class name. The name can be fully qualified or just the bare class name. If the bare name is given, the class should …

Methods

def final(self, state): Inherited from: SearchAgent.final

Inform the agent about the result of a game.
def getAction(self, state): Inherited from: SearchAgent.getAction

Returns the next action in the path chosen earlier (in registerInitialState). Return Directions.STOP if there is no further action to take.
def observationFunction(self, state): Inherited from: SearchAgent.observationFunction

Make an observation on the state of the game. Called once for each round of the game.
def registerInitialState(self, state): Inherited from: SearchAgent.registerInitialState

This is the first time that the agent sees the layout of the game board. Here, we choose a path to the goal. In this phase, the agent should compute …