Tools for structuring and scaling research into algorithmic competition.
Components:
- Reinforcement learning models of algorithmic competition
import AlgorithmicCompetition
using Distributed
n_procs_ = 2 # update number of parallel processes
_procs = addprocs(
n_procs_,
topology = :master_worker,
exeflags = ["--threads=1", "--project=$(Base.active_project())"],
)
@everywhere begin
using Pkg
Pkg.instantiate()
using AlgorithmicCompetition
end
aiapc_results = AlgorithmicCompetition.run_aiapc()
For citations of works this project is based on, see citations.bib
.
tmux
TASK=DDDC bash src/run_pc2.sh
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