tests pass

Author: zsunberg

Project.toml

@@ -10,13 +10,14 @@ POMDPTesting = "92e6a534-49c2-5324-9027-86e3c861ab81"
 POMDPs = "a93abf59-7444-517b-a68a-c42f96afdd7d"
 
 [compat]
-julia = "1"
 POMDPModelTools = ">=0.1.6"
+julia = "1"
 
 [extras]
 POMDPPolicies = "182e52fb-cfd0-5e46-8c26-fd0667c990f4"
 POMDPSimulators = "e0d0a172-29c6-5d4e-96d0-f262df5d01fd"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 
 [targets]
-test = ["Test", "POMDPPolicies", "POMDPSimulators"]
+test = ["Test", "POMDPPolicies", "POMDPSimulators", "Random"]

src/discrete_explicit.jl

@@ -72,9 +72,9 @@ Create a POMDP defined by the tuple (S,A,O,T,Z,R,γ).
 - `b₀=Uniform(S)`: Initial belief/state distribution (See `POMDPModelTools.Deterministic` and `POMDPModelTools.SparseCat` for other options).
 
 ## Keyword
-- `terminal=Set()`: Set of terminal states. Once a terminal state is reached, no more actions can be taken or reward received.
+- `terminals=Set()`: Set of terminal states. Once a terminal state is reached, no more actions can be taken or reward received.
 """
-function DiscreteExplicitPOMDP(s, a, o, t, z, r, discount, b0=Uniform(s))
+function DiscreteExplicitPOMDP(s, a, o, t, z, r, discount, b0=Uniform(s); terminals=Set())
     ss = vec(collect(s))
     as = vec(collect(a))
     os = vec(collect(o))
@@ -108,7 +108,7 @@ function DiscreteExplicitPOMDP(s, a, o, t, z, r, discount, b0=Uniform(s))
         Dict(ss[i]=>i for i in 1:length(ss)),
         Dict(as[i]=>i for i in 1:length(as)),
         Dict(os[i]=>i for i in 1:length(os)),
-        discount, b0, terminal
+        discount, b0, convert(Set{eltype(ss)}, terminals)
     )
 
     probability_check(m)
@@ -133,9 +133,9 @@ Create an MDP defined by the tuple (S,A,T,R,γ).
 - `p₀=Uniform(S)`: Initial state distribution (See `POMDPModelTools.Deterministic` and `POMDPModelTools.SparseCat` for other options).
 
 ## Keyword
-- `terminal=Set()`: Set of terminal states. Once a terminal state is reached, no more actions can be taken or reward received.
+- `terminals=Set()`: Set of terminal states. Once a terminal state is reached, no more actions can be taken or reward received.
 """
-function DiscreteExplicitMDP(s, a, t, r, discount, p0=Uniform(s); terminal=Set())
+function DiscreteExplicitMDP(s, a, t, r, discount, p0=Uniform(s); terminals=Set())
     ss = vec(collect(s))
     as = vec(collect(a))
 
@@ -145,7 +145,7 @@ function DiscreteExplicitMDP(s, a, t, r, discount, p0=Uniform(s); terminal=Set()
         ss, as, tds, r,
         Dict(ss[i]=>i for i in 1:length(ss)),
         Dict(as[i]=>i for i in 1:length(as)),
-        discount, p0, terminal
+        discount, p0, convert(Set{eltype(ss)}, terminals)
     )
 
     trans_prob_consistency_check(m)

test/discrete_explicit.jl

@@ -50,7 +50,7 @@
 
     dm = DiscreteExplicitPOMDP(S,A,O,T,Z,R,γ,Deterministic(:left))
     @test initialstate(dm, Random.GLOBAL_RNG) == :left
-    tm = DiscreteExplicitPOMDP(S,A,O,T,Z,R,γ,terminal=Set(S))
+    tm = DiscreteExplicitPOMDP(S,A,O,T,Z,R,γ,terminals=Set(S))
     @test isterminal(tm, initialstate(tm, Random.GLOBAL_RNG))
 end
 
@@ -80,7 +80,7 @@ end
 
     m = DiscreteExplicitMDP(S,A,T,R,γ)
     m = DiscreteExplicitMDP(S,A,T,R,γ,p₀)
-    m = DiscreteExplicitMDP(S,A,T,R,γ,p₀,terminal=Set(5))
+    m = DiscreteExplicitMDP(S,A,T,R,γ,p₀,terminals=Set(5))
     @test isterminal(m, 5)
 
     solver = FunctionSolver(x->1)

test/runtests.jl

@@ -1,6 +1,11 @@
 using QuickPOMDPs
 using Test
 
-using POMDPs, POMDPPolicies, POMDPSimulators, BeliefUpdaters
+using POMDPs
+using POMDPPolicies
+using POMDPSimulators
+using BeliefUpdaters
+using POMDPModelTools
+using Random
 
 include("discrete_explicit.jl")