diff --git a/environments/environment.jl b/environments/environment.jl
index ae813ea79..94d1ddb8e 100644
--- a/environments/environment.jl
+++ b/environments/environment.jl
@@ -31,7 +31,7 @@ mutable struct Environment{X,T,M,A,O,I}
     dynamics_jacobian_state::Matrix{T}
     dynamics_jacobian_input::Matrix{T}
     input_previous::Vector{T}
-	control_map::Matrix{T}
+    control_map::Matrix{T}
     num_states::Int
     num_inputs::Int
     num_observations::Int
@@ -66,33 +66,33 @@ end
     attitude_decompress: flag for pre- and post-concatenating Jacobians with attitude Jacobians
 """
 function Base.step(env::Environment, x, u;
-    gradients=false,
-    attitude_decompress=false)
+    gradients = false,
+    attitude_decompress = false)
 
     mechanism = env.mechanism
-    timestep= mechanism.timestep
+    timestep = mechanism.timestep
 
     x0 = x
     # u = clip(env.input_space, u) # control limits
     env.input_previous .= u  # for rendering in Gym
-	u_scaled = env.control_map * u
+    u_scaled = env.control_map * u
 
     z0 = env.representation == :minimal ? minimal_to_maximal(mechanism, x0) : x0
-    z1 = step!(mechanism, z0, u_scaled; opts=env.opts_step)
+    z1 = step!(mechanism, z0, u_scaled; opts = env.opts_step)
     env.state .= env.representation == :minimal ? maximal_to_minimal(mechanism, z1) : z1
 
     # Compute cost
     costs = cost(env, x, u)
 
-	# Check termination
-	done = is_done(env, x)
+    # Check termination
+    done = is_done(env, x)
 
     # Gradients
     if gradients
         if env.representation == :minimal
-            fx, fu = get_minimal_gradients!(env.mechanism, z0, u_scaled, opts=env.opts_grad)
+            fx, fu = get_minimal_gradients!(env.mechanism, z0, u_scaled, opts = env.opts_grad)
         elseif env.representation == :maximal
-            fx, fu = get_maximal_gradients!(env.mechanism, z0, u_scaled, opts=env.opts_grad)
+            fx, fu = get_maximal_gradients!(env.mechanism, z0, u_scaled, opts = env.opts_grad)
             if attitude_decompress
                 A0 = attitude_jacobian(z0, length(env.mechanism.bodies))
                 A1 = attitude_jacobian(z1, length(env.mechanism.bodies))
@@ -109,11 +109,11 @@ function Base.step(env::Environment, x, u;
 end
 
 function Base.step(env::Environment, u;
-    gradients=false, 
-    attitude_decompress=false) 
-    step(env, env.state, u; 
-        gradients=gradients, 
-        attitude_decompress=attitude_decompress)
+    gradients = false,
+    attitude_decompress = false)
+    step(env, env.state, u;
+        gradients = gradients,
+        attitude_decompress = attitude_decompress)
 end
 
 """
@@ -156,7 +156,7 @@ is_done(env::Environment, x) = false
     x: state
 """
 function Base.reset(env::Environment{X};
-    x=nothing) where X
+    x = nothing) where {X}
 
     initialize!(env.mechanism, type2symbol(X))
     if x != nothing
@@ -172,14 +172,14 @@ function Base.reset(env::Environment{X};
     return get_observation(env)
 end
 
-function MeshCat.render(env::Environment, 
-    mode="human")
+function MeshCat.render(env::Environment,
+    mode = "human")
     z = env.representation == :minimal ? minimal_to_maximal(env.mechanism, env.state) : env.state
-    set_robot(env.vis, env.mechanism, z, name=:robot)
+    set_robot(env.vis, env.mechanism, z, name = :robot)
     return nothing
 end
 
-function seed(env::Environment, s=0)
+function seed(env::Environment, s = 0)
     env.rng[1] = MersenneTwister(s)
     return nothing
 end
@@ -214,26 +214,20 @@ mutable struct BoxSpace{T,N} <: Space{T,N}
     dtype::DataType # this is always T, it's needed to interface with Stable-Baselines
 end
 
-function BoxSpace(n::Int; low::AbstractVector{T} = -ones(n), high::AbstractVector{T} = ones(n)) where T
+function BoxSpace(n::Int; low::AbstractVector{T} = -ones(n), high::AbstractVector{T} = ones(n)) where {T}
     return BoxSpace{T,n}(n, low, high, (n,), T)
 end
 
 function sample(s::BoxSpace{T,N}) where {T,N}
-    return rand(T,N) .* (s.high .- s.low) .+ s.low
+    return rand(T, N) .* (s.high .- s.low) .+ s.low
 end
 
 function contains(s::BoxSpace{T,N}, v::AbstractVector{T}) where {T,N}
     all(v .>= s.low) && all(v .<= s.high)
 end
 
-# For compat with RLBase
-Base.length(s::BoxSpace) = s.n
-Base.in(v::AbstractVector{T}, s::BoxSpace{T,N}) where {T,N} = all(v .>= s.low) && all(v .<= s.high)
-Random.rand(rng::Random.AbstractRNG, s::BoxSpace{T,N}) where {T,N} = return rand(rng, T,N) .* (s.high .- s.low) .+ s.low
-
 function clip(s::BoxSpace, u)
     clamp.(u, s.low, s.high)
 end
 
-
-
+Random.rand(rng::Random.AbstractRNG, s::BoxSpace{T,N}) where {T,N} = return rand(rng, T, N) .* (s.high .- s.low) .+ s.low
diff --git a/environments/rlenv.jl b/environments/rlenv.jl
index 947026973..3baf47d12 100644
--- a/environments/rlenv.jl
+++ b/environments/rlenv.jl
@@ -17,8 +17,12 @@ function DojoRLEnv(name::String; kwargs...)
     DojoRLEnv(Dojo.get_environment(name; kwargs...))
 end
 
-RLBase.action_space(env::DojoRLEnv) = env.dojoenv.input_space
-RLBase.state_space(env::DojoRLEnv) = env.dojoenv.observation_space
+function Base.convert(::Type{RLBase.Space}, s::BoxSpace)
+    RLBase.Space([BoxSpace(1; low = s.low[i:i], high = s.high[i:i]) for i in 1:s.n])
+end
+
+RLBase.action_space(env::DojoRLEnv) = convert(RLBase.Space, env.dojoenv.input_space)
+RLBase.state_space(env::DojoRLEnv) = convert(RLBase.Space, env.dojoenv.observation_space)
 RLBase.is_terminated(env::DojoRLEnv) = env.done
 
 RLBase.reset!(env::DojoRLEnv) = reset(env.dojoenv)
@@ -39,4 +43,4 @@ function (env::DojoRLEnv)(a)
     env.info = i
     return nothing
 end
-(env::DojoRLEnv)(a::AbstractFloat) = env([a])
+(env::DojoRLEnv)(a::Number) = env([a])