46 lines
1.7 KiB
Plaintext
46 lines
1.7 KiB
Plaintext
TRAINING
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1. Load pre-trained massive set of transitions
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-- For all roundabouts
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-- For all tracks
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-- For all vehicles
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-- For all valid timesteps
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-- Rasterized state (incl. path), action
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2. HGAIL
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-- For each epoch
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-- INSTANTIATE A NEW ENVIRONMENT (Roundabout + Track) w/ randomized agent, from set of all expert environments
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-- Train discriminator off training data + yielded low-level transitions
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-- Train generator off yielded high-level transitions + summed low-level discriminator rewards
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TESTING
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1. Save average vehicle velocities for all expert vehicles (loop roundabout + track + vehicle, average over time)
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2. Run test suite for: expert, BC, GAIL, RAIL, HGAIL, (and hopefully HRAIL)
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-- For all roundabouts, tracks
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-- Get expert velocities for track
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-- Simulate incrementing agent environment (e.g. on reset, agent +=1)
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-- Store low-level true joint states, actions, and controlled vehicle index
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-- Per-vehicle statistics (v_all, v_mean, v_shortfall, a_all, jerk_all, n_collisions, T)
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-- Aggregate statistics + joint
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Problems
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-----------
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Should train without stopping for collisions, however when doing so, end up with policy that always takes decelerate option
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-- It seems safe at the start of each vehicles sim, but actually it isn't since a car will spawn and hit it
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Solutions:
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-- Hold cars from spawning if their spawn location is full
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-- Start simulations a few seconds later (after cars clear their spawn places)
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Save massive set of transition raw states beforehand (1 from training, but with raw states)
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# -- For all roundabouts, tracks
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# -- For all vehicles, steps
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# -- Raw vehicle state, action |