Tiles

Rectangular Tiles

class Tiles(x_range, n_tiles, state_components=None)

Bases: object

Class implementing rectangular tiling. For each point in the state space, this class can be used to compute the index of the corresponding tile.

__init__(x_range, n_tiles, state_components=None)

Constructor.

Parameters:

• x_range (list) – list of two-elements lists specifying the range of each state variable;

• n_tiles (list) – list of the number of tiles to be used for each dimension.

• state_components (list, None) – list of the dimensions of the input to be considered by the tiling. The number of elements must match the number of elements in x_range and n_tiles.

__call__(x)

Call self as a function.

static generate(n_tilings, n_tiles, low, high, uniform=False)

Factory method to build n_tilings tilings of n_tiles tiles with a range between low and high for each dimension.

Parameters:

• n_tilings (int) – number of tilings, or -1 to compute the number automatically;

• n_tiles (list) – number of tiles for each tilings for each dimension;

• low (np.ndarray) – lowest value for each dimension;

• high (np.ndarray) – highest value for each dimension.

• uniform (bool, False) – if True the displacement for each tiling will be w/n_tilings, where w is the tile width. Otherwise, the displacement will be k*w/n_tilings, where k=2i+1, where i is the dimension index.

Returns:

The list of the generated tiles.

Voronoi Tiles

class VoronoiTiles(prototypes)

Bases: object

Class implementing voronoi tiling. For each point in the state space, this class can be used to compute the index of the corresponding tile.

__init__(prototypes)

Constructor.

Parameters:

prototypes (list) – list of prototypes to compute the partition.

__call__(x)

Call self as a function.

static generate(n_tilings, n_prototypes, low=None, high=None, mu=None, sigma=None)

Factory method to build n_tilings tilings of n_prototypes. Prototypes are generated randomly sampled. If low and high are provided, prototypes are sampled uniformly between low and high, otherwise mu and sigma must be specified and prototypes are sampled from the corresponding Gaussian.

Parameters:

• n_tilings (int) – number of tilings, or -1 to compute the number automatically;

• n_prototypes (list) – number of prototypes for each tiling;

• low (np.ndarray, None) – lowest value for each dimension, needed for uniform sampling;

• high (np.ndarray, None) – highest value for each dimension, needed for uniform sampling.

• mu (np.ndarray, None) – mean value for each dimension, needed for Gaussian sampling.

• sigma (np.ndarray, None) – variance along each dimension, needed for Gaussian sampling.

Returns:

The list of the generated tiles.