Remove the phased agent code - #190
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The EMPIRIC agent and its baselines all run under the continual protocol. This removes the phased experiment path (learn sessions between online learning cycles, solve sessions per test task) and the code only it reached: - AgentModelBasedApproach, the agent explorers, the subgoal-annotation execution monitor and the sampler learning mixin - the NL world model and GNN dynamics baselines - the Docker sandbox backend and the sampler synthesis tools - the learn-note templates, the oracle-simulator branches, the per-cycle fit diagnostics, and the settings flags nothing reads anymore AgentModelFreeApproach keeps the option model, tool-context sync and checkpointing that the continual arms inherit. Its task solver raises, since the arms play levels through ContinualPlayMixin.play_level. ExoPredicator-era code is untouched.
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Summary
Stacked on #189 (base
empiric-configs); review and merge after it.The EMPIRIC agent and its six baselines all run under the continual protocol, where each arm plays the levels of one environment through
ContinualPlayMixin.play_level.This deletes the phased experiment path (learn sessions between online learning cycles, solve sessions per test task) and the code only that path reached: 70 files, about 12.8k lines.
Deleted:
AgentModelBasedApproach, the agent explorers and their base class, and thesubgoal_annotationsexecution monitor;SamplerLearningMixinand the sampler synthesis tools;AgentSimLearningApproach: the methods only the phased path called, the oracle-simulator branches, and the per-cycle fit diagnostics with their fields;Kept:
AgentModelFreeApproachkeeps the option model, tool-context sync and checkpointing that the continual arms inherit. Its_solvenow raises, since no arm solves tasks outsideplay_level.ExoPredicatortag or at the upstream fork point.Sketch refinement now draws a step's params from its ground sampler, or uniformly; the learned parameterized samplers were phased-only.
empiric/common.yamlandenvs.yamlstop setting the phased pipeline's flags (make_*_videos,num_online_learning_cycles,max_num_steps_interaction_request, the online early-stopping flags,online_nsrt_learning_requests_per_cycle).Under the continual protocol
run_pipelinereturns right afterrun_continual, so none of them was read.Tests of deleted code are deleted.
test_execution_monitoring.pyreturns to its upstream version, and the interaction-request bookkeeping test now exercises the online process learner, the remaining implementer of that hook.Test plan
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