more tests

test/runtests.jl

@@ -4,4 +4,47 @@ using Base.Test
 solver = POMDPSolveSolver()
 pomdp = POMDPSolveFile(Pkg.dir("POMDPSolve", "test", "tiger.pomdp"))
 policy = POMDPSolvePolicy("mypolicy.policy")
+solve(solver, pomdp, policy)
+
+# NOTe: following are arbitrarily set, values are probably not useful
+solver2 = POMDPSolveSolver(
+    stdout = "out.txt",                 # Redirect programs stdout to a file of this name
+    rand_seed = (1,2,3),                # Set the random seed for program execution
+    stat_summary=true,                  # Whether to keep and print internal execution stats
+    memory_limit = 10000,               # Set upper bound memory usage
+    time_limit = 10000,                 # Set upper bound on execution time
+    horizon = 10,                       # Sets the number of iterations of value iteration
+    discount = 0.9,                     # Set the discount fact to use in value iteration
+    stop_criteria = :weak,              # Sets the value iteration stopping criteria
+    stop_delta = 0.01,                  # Sets the precision for the stopping criteria check
+    save_all = true,                    # Sets whether or not to save every iteration's solution
+    vi_variation = :adjustable_epsilon, # Sets the general category of value iteration to use
+    start_epsilon = 0.01,               # Sets the starting precision for adjustable epsilon VI
+    end_epsilon = 0.02,                 # Sets the ending precision for adjustable epsilon VI
+    epsilon_adjust = 0.01,              # Sets the precision increment for adjustable epsilon VI
+    max_soln_size = 1000.0,             # Sets the max size for the fixed solution size VI
+    history_length = 2,                 # Sets history window to use for adjustable epsilon VI
+    history_delta = 1,                  # Sets solution size delta to use for adjustable epsilon VI
+    dom_check = false,                  # Controls whether simple domination check is done or not
+    prune_epsilon = 1e-6,               # Sets the precision level for the prune operations
+    epsilon = 1e-6,                     # General solution precision level setting
+    lp_epsilon = 1e-6,                  # Precision use in linear programs
+    proj_purge = :normal,               # Type of pruning to use for pre-iteration solving
+    q_purge = :normal,                  # Type of pruning to use for a post-iteration solving
+    witness_points = true,              # Whether to include 'witness points' in solving
+    alg_rand = 10,                      # How many points to use to seed value function creation
+    prune_rand = 10,                    # How many points to use to seed pruning process
+    method = :witness,                  # Selects the main solution algorithm to use
+    enum_purge = :epsilon_prune,        # The pruning method to use when using the 'enum' algorithm
+    inc_prune = :generalized,           # The variation of the incremental pruning algorithm
+    fg_type = :pairwise,                # Finite grid method means to generate belief points
+    fg_points = 10,                     # Maximal number of belief points to use in finite grid
+    fg_save = true,                     # Whether to save the points used in finite grid
+    mcgs_traj_length = 2,               # Trajectory length for Monte Carlo belief generation
+    mcgs_num_traj = 10,                 # Number of trajectories for Monte Carlo belief generation
+    mcgs_traj_iter_count = 10,          # Times to iterate on a trajectory for MCGS method
+    mcgs_prune_freq = 2,                # How frequently to prune during MCGS method
+    fg_purge = :pairwise,               # Finite grid method means to prune value functions
+    verbose = :witness,                 # Turns on extra debugging output for a module
+    )
 solve(solver, pomdp, policy)