final paper updates and version update

JuliaPOMDP · Jul 18, 2024 · d06bc7c · d06bc7c
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diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "CompressedBeliefMDPs"
 uuid = "0a809e47-b8eb-4578-b4e8-4c2c5f9f833c"
 authors = ["Logan-Mondal-Bhamidipaty"]
-version = "1.1.0"
+version = "1.1.1"
 
 [deps]
 Bijections = "e2ed5e7c-b2de-5872-ae92-c73ca462fb04"

diff --git a/paper.md b/paper.md
@@ -43,7 +43,7 @@ CompressedBeliefMDPs.jl is a modular generalization of the original algorithm. I
 
 ### Belief Compression
 
-CompressedBeliefMDPs.jl abstracts the belief compression algorithm of @Roy into four steps: sampling, compression, construction, and planning. The `Sampler` abstract type handles belief sampling; the `Compressor` abstract type handles belief compression; the `CompressedBeliefMDP` struct handles constructing the compressed belief MDP; and the `CompressedBeliefSolver` and `CompressedBeliefPolicy` structs handle planning in the compressed belief MDP. 
+CompressedBeliefMDPs.jl abstracts the belief compression algorithm of @Roy into four steps: sampling, compression, construction, and planning. The `Sampler` abstract type handles belief sampling; the `Compressor` abstract type handles belief compression; the `CompressedBeliefMDP` struct handles constructing the compressed belief-state MDP; and the `CompressedBeliefSolver` and `CompressedBeliefPolicy` structs handle planning in the compressed belief-state MDP. 
 
 Our framework is a generalization of the original belief compression algorithm. @Roy uses a heuristic controller for sampling beliefs; exponential family principal component analysis with Poisson loss for compression [@EPCA]; and local approximation value iteration for the base solver. CompressedBeliefMDPs.jl, on the other hand, is a modular framework, meaning that belief compression can be applied with *any* combination of sampler, compressor, and MDP solver.