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https://gitlab.rlp.net/mobitar/ReCo.jl.git
synced 2024-12-30 17:43:34 +00:00
back to local center of mass with reward as distance to it
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parent
275b69c928
commit
9c00da84ea
1 changed files with 61 additions and 65 deletions
126
src/RL.jl
126
src/RL.jl
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@ -44,20 +44,15 @@ mutable struct Env <: AbstractEnv
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distance_state_space::Vector{Interval}
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direction_angle_state_space::Vector{Interval}
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position_angle_state_space::Vector{Interval}
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n_states::Int64
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state_space::Vector{SVector{3,Interval}}
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state_space::Vector{SVector{2,Interval}}
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state_ind_space::OneTo{Int64}
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state_ind::Int64
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reward::Float64
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terminated::Bool
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center_of_mass::SVector{2,Float64} # TODO: Use or remove
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gyration_tensor_eigvec_to_smaller_eigval::SVector{2,Float64}
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gyration_tensor_eigvec_to_bigger_eigval::SVector{2,Float64}
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function Env(;
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max_distance::Float64,
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min_distance::Float64=0.0,
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@ -65,9 +60,8 @@ mutable struct Env <: AbstractEnv
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n_ω_actions::Int64=3,
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max_v::Float64=40.0,
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max_ω::Float64=π / 2,
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n_distance_states::Int64=4,
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n_distance_states::Int64=3,
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n_direction_angle_states::Int64=3,
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n_position_angle_states::Int64=8,
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)
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@assert min_distance >= 0.0
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@assert max_distance > min_distance
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@ -77,7 +71,6 @@ mutable struct Env <: AbstractEnv
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@assert max_ω > 0
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@assert n_distance_states > 1
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@assert n_direction_angle_states > 1
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@assert n_position_angle_states > 1
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v_action_space = range(; start=0.0, stop=max_v, length=n_v_actions)
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ω_action_space = range(; start=-max_ω, stop=max_ω, length=n_ω_actions)
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@ -115,23 +108,19 @@ mutable struct Env <: AbstractEnv
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end
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direction_angle_state_space = angle_state_space(n_direction_angle_states)
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position_angle_state_space = angle_state_space(n_position_angle_states)
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n_states = n_distance_states * n_direction_angle_states * n_position_angle_states
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n_states = n_distance_states * n_direction_angle_states + 1
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state_space = Vector{SVector{3,Interval}}(undef, n_states)
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state_space = Vector{SVector{2,Interval}}(undef, n_states - 1)
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ind = 1
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for distance_state in distance_state_space
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for direction_angle_state in direction_angle_state_space
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for position_angle_state in position_angle_state_space
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state_space[ind] = SVector(
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distance_state, direction_angle_state, position_angle_state
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)
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ind += 1
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end
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state_space[ind] = SVector(distance_state, direction_angle_state)
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ind += 1
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end
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end
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# Last state is when no particle is in the skin radius
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state_ind_space = OneTo(n_states)
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@ -141,21 +130,18 @@ mutable struct Env <: AbstractEnv
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action_ind_space,
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distance_state_space,
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direction_angle_state_space,
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position_angle_state_space,
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n_states,
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state_space,
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state_ind_space,
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INITIAL_STATE_IND,
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INITIAL_REWARD,
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false,
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SVector(0.0, 0.0),
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)
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end
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end
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function reset!(env::Env)
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env.state_ind = env.n_states
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env.reward = INITIAL_REWARD
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env.terminated = false
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return nothing
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@ -187,8 +173,10 @@ struct Params{H<:AbstractHook}
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goal_gyration_tensor_eigvals_ratio::Float64
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n_particles::Int64
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half_box_len::Float64
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max_elliptic_distance::Float64
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max_distance::Float64
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vec_to_neighbour_sums::Vector{SVector{2,Float64}}
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n_neighbours::Vector{Int64}
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function Params(
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env::Env,
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@ -197,10 +185,8 @@ struct Params{H<:AbstractHook}
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n_steps_before_actions_update::Int64,
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goal_gyration_tensor_eigvals_ratio::Float64,
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n_particles::Int64,
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half_box_len::Float64,
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max_distance::Float64,
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) where {H<:AbstractHook}
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max_elliptic_distance = sqrt(2) * half_box_len
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n_states = env.n_states
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return new{H}(
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@ -214,23 +200,35 @@ struct Params{H<:AbstractHook}
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n_steps_before_actions_update,
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goal_gyration_tensor_eigvals_ratio,
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n_particles,
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half_box_len,
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max_elliptic_distance,
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max_distance,
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fill(SVector(0.0, 0.0), n_particles),
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fill(0, n_particles),
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)
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end
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end
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function pre_integration_hook(rl_params::Params)
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@simd for id in 1:(rl_params.n_particles)
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rl_params.vec_to_neighbour_sums[id] = SVector(0.0, 0.0)
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rl_params.n_neighbours[id] = 0
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end
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return nothing
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end
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function state_update_helper_hook(
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rl_params::Params, id1::Int64, id2::Int64, r⃗₁₂::SVector{2,Float64}
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)
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rl_params.vec_to_neighbour_sums[id1] += r⃗₁₂
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rl_params.vec_to_neighbour_sums[id2] -= r⃗₁₂
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rl_params.n_neighbours[id1] += 1
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rl_params.n_neighbours[id2] += 1
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return nothing
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end
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function find_state_ind(state::S, state_space::Vector{S}) where {S<:SVector{3,Interval}}
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function find_state_ind(state::S, state_space::Vector{S}) where {S<:SVector{2,Interval}}
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return findfirst(x -> x == state, state_space)
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end
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@ -249,44 +247,35 @@ function state_update_hook(rl_params::Params, particles::Vector{Particle})
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env = rl_params.env
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env.center_of_mass = Shape.center_of_mass(particles, rl_params.half_box_len)
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for id in 1:(rl_params.n_particles)
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particle = particles[id]
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n_neighbours = rl_params.n_neighbours[id]
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vec_to_center_of_mass = ReCo.minimum_image(
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env.center_of_mass - particle.c, rl_params.half_box_len
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)
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if n_neighbours == 0
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state_ind = env.n_states
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else
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vec_to_local_center_of_mass = rl_params.vec_to_neighbour_sums[id] / n_neighbours
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distance = sqrt(vec_to_center_of_mass[1]^2 + vec_to_center_of_mass[2]^2)
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distance = sqrt(
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vec_to_local_center_of_mass[1]^2 + vec_to_local_center_of_mass[2]^2
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)
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distance_state = find_state_interval(distance, env.distance_state_space)
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distance_state = find_state_interval(distance, env.distance_state_space)
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si, co = sincos(particles[id].φ)
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si, co = sincos(particles[id].φ)
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direction_angle = angle2(SVector(co, si), vec_to_center_of_mass)
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position_angle = atan(-vec_to_center_of_mass[2], -vec_to_center_of_mass[1])
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direction_angle = angle2(SVector(co, si), vec_to_local_center_of_mass)
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direction_angle_state = find_state_interval(
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direction_angle, env.direction_angle_state_space
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)
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position_angle_state = find_state_interval(
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position_angle, env.position_angle_state_space
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)
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direction_angle_state = find_state_interval(
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direction_angle, env.direction_angle_state_space
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)
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state = SVector{3,Interval}(
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distance_state, direction_angle_state, position_angle_state
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)
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state_ind = find_state_ind(state, env.state_space)
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state = SVector{2,Interval}(distance_state, direction_angle_state)
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state_ind = find_state_ind(state, env.state_space)
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end
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rl_params.states_ind[id] = state_ind
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end
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v1, v2 = Shape.gyration_tensor_eigvecs(particles, rl_params.half_box_len) # TODO: Reuse center_of_mass
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env.gyration_tensor_eigvec_to_smaller_eigval = v1
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env.gyration_tensor_eigvec_to_bigger_eigval = v2
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return nothing
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end
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@ -295,13 +284,19 @@ function get_env_agent_hook(rl_params::Params)
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end
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function update_reward!(env::Env, rl_params::Params, particle::Particle)
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env.reward =
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-Shape.elliptical_distance(
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particle,
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env.gyration_tensor_eigvec_to_smaller_eigval,
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env.gyration_tensor_eigvec_to_bigger_eigval,
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rl_params.goal_gyration_tensor_eigvals_ratio,
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) / (rl_params.max_elliptic_distance^2 * rl_params.n_particles)
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id = particle.id
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normalization = (rl_params.max_distance * rl_params.n_particles)
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n_neighbours = rl_params.n_neighbours[id]
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if n_neighbours == 0
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env.reward = -(rl_params.max_distance^2) / normalization
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else
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vec_to_local_center_of_mass = rl_params.vec_to_neighbour_sums[id] / n_neighbours # TODO: Reuse vec_to_local_center_of_mass from state_update_hook
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env.reward =
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-(vec_to_local_center_of_mass[1]^2 + vec_to_local_center_of_mass[2]^2) /
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normalization
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end
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return nothing
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end
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@ -403,11 +398,12 @@ function run_rl(;
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Random.seed!(seed)
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sim_consts = ReCo.gen_sim_consts(
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n_particles, 0.0; skin_to_interaction_r_ratio=1.5, packing_ratio=0.22
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n_particles, 0.0; skin_to_interaction_r_ratio=2.0, packing_ratio=0.22
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)
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n_particles = sim_consts.n_particles
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env = Env(; max_distance=sqrt(2) * sim_consts.half_box_len)
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max_distance = sim_consts.skin_r
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env = Env(; max_distance=max_distance)
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agent = gen_agent(env.n_states, env.n_actions, ϵ_stable)
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@ -422,7 +418,7 @@ function run_rl(;
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n_steps_before_actions_update,
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goal_gyration_tensor_eigvals_ratio,
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n_particles,
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sim_consts.half_box_len,
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max_distance,
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)
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parent_dir = "RL" * parent_dir
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